transformers tensorboard safetensors t5 text2text-generation generated_from_trainer base_model:t5-small license:apache-2.0 autotrain_compatible endpoints_compatible text-generation-inference region:us
---
license: apache-2.0
base_model: t5-small
tags:
- generated_from_trainer
metrics:
- bleu
model-index:
- name: bic-tl-model
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# bic-tl-model

This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0000
- Bleu: 8.6577
- Gen Len: 9.5337

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 0.001
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 200
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Bleu   | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|
| No log        | 1.0   | 11   | 2.8101          | 0.4192 | 9.6933  |
| No log        | 2.0   | 22   | 2.4413          | 0.5091 | 9.8896  |
| No log        | 3.0   | 33   | 2.1777          | 0.5912 | 9.9939  |
| No log        | 4.0   | 44   | 1.9031          | 0.7161 | 9.7791  |
| No log        | 5.0   | 55   | 1.6391          | 0.5207 | 9.6564  |
| No log        | 6.0   | 66   | 1.4137          | 0.8978 | 9.6135  |
| No log        | 7.0   | 77   | 1.1997          | 1.1307 | 9.6135  |
| No log        | 8.0   | 88   | 1.0269          | 1.4498 | 9.638   |
| No log        | 9.0   | 99   | 0.8257          | 1.9986 | 9.7423  |
| No log        | 10.0  | 110  | 0.6801          | 2.1989 | 9.4417  |
| No log        | 11.0  | 121  | 0.5581          | 2.5771 | 9.6687  |
| No log        | 12.0  | 132  | 0.4526          | 2.7754 | 9.5951  |
| No log        | 13.0  | 143  | 0.3840          | 3.3881 | 9.4479  |
| No log        | 14.0  | 154  | 0.3263          | 3.767  | 9.589   |
| No log        | 15.0  | 165  | 0.2600          | 4.1389 | 9.5399  |
| No log        | 16.0  | 176  | 0.1992          | 4.6642 | 9.4785  |
| No log        | 17.0  | 187  | 0.1552          | 5.3166 | 9.4724  |
| No log        | 18.0  | 198  | 0.1273          | 5.5679 | 9.5153  |
| No log        | 19.0  | 209  | 0.0899          | 6.497  | 9.4724  |
| No log        | 20.0  | 220  | 0.0848          | 6.5853 | 9.6074  |
| No log        | 21.0  | 231  | 0.0564          | 7.0719 | 9.4847  |
| No log        | 22.0  | 242  | 0.0583          | 7.1069 | 9.5521  |
| No log        | 23.0  | 253  | 0.0379          | 7.6262 | 9.5521  |
| No log        | 24.0  | 264  | 0.0362          | 7.2957 | 9.5031  |
| No log        | 25.0  | 275  | 0.0341          | 8.1019 | 9.5767  |
| No log        | 26.0  | 286  | 0.0320          | 8.1036 | 9.6012  |
| No log        | 27.0  | 297  | 0.0166          | 8.3655 | 9.5337  |
| No log        | 28.0  | 308  | 0.0190          | 8.1402 | 9.5337  |
| No log        | 29.0  | 319  | 0.0123          | 8.2834 | 9.5399  |
| No log        | 30.0  | 330  | 0.0104          | 8.4782 | 9.5337  |
| No log        | 31.0  | 341  | 0.0092          | 8.1852 | 9.5337  |
| No log        | 32.0  | 352  | 0.0086          | 8.5036 | 9.5276  |
| No log        | 33.0  | 363  | 0.0057          | 8.3105 | 9.5337  |
| No log        | 34.0  | 374  | 0.0049          | 8.3607 | 9.5337  |
| No log        | 35.0  | 385  | 0.0055          | 8.3729 | 9.5399  |
| No log        | 36.0  | 396  | 0.0070          | 8.5598 | 9.546   |
| No log        | 37.0  | 407  | 0.0088          | 8.1822 | 9.5276  |
| No log        | 38.0  | 418  | 0.0061          | 8.2457 | 9.5276  |
| No log        | 39.0  | 429  | 0.0054          | 8.4559 | 9.5276  |
| No log        | 40.0  | 440  | 0.0052          | 8.6455 | 9.5399  |
| No log        | 41.0  | 451  | 0.0065          | 8.6455 | 9.5399  |
| No log        | 42.0  | 462  | 0.0017          | 8.6577 | 9.5337  |
| No log        | 43.0  | 473  | 0.0035          | 8.638  | 9.5337  |
| No log        | 44.0  | 484  | 0.0022          | 8.6577 | 9.5337  |
| No log        | 45.0  | 495  | 0.0016          | 8.5791 | 9.5337  |
| 0.7779        | 46.0  | 506  | 0.0025          | 8.5791 | 9.5337  |
| 0.7779        | 47.0  | 517  | 0.0014          | 8.5791 | 9.5337  |
| 0.7779        | 48.0  | 528  | 0.0015          | 8.5791 | 9.5337  |
| 0.7779        | 49.0  | 539  | 0.0022          | 8.4109 | 9.5337  |
| 0.7779        | 50.0  | 550  | 0.0014          | 8.591  | 9.5337  |
| 0.7779        | 51.0  | 561  | 0.0021          | 8.6455 | 9.5399  |
| 0.7779        | 52.0  | 572  | 0.0011          | 8.6577 | 9.5337  |
| 0.7779        | 53.0  | 583  | 0.0010          | 8.6577 | 9.5337  |
| 0.7779        | 54.0  | 594  | 0.0016          | 8.6036 | 9.5337  |
| 0.7779        | 55.0  | 605  | 0.0009          | 8.6083 | 9.5337  |
| 0.7779        | 56.0  | 616  | 0.0007          | 8.6577 | 9.5337  |
| 0.7779        | 57.0  | 627  | 0.0009          | 8.6577 | 9.5337  |
| 0.7779        | 58.0  | 638  | 0.0035          | 8.653  | 9.5337  |
| 0.7779        | 59.0  | 649  | 0.0007          | 8.6577 | 9.5337  |
| 0.7779        | 60.0  | 660  | 0.0003          | 8.6577 | 9.5337  |
| 0.7779        | 61.0  | 671  | 0.0004          | 8.6577 | 9.5337  |
| 0.7779        | 62.0  | 682  | 0.0007          | 8.6577 | 9.5337  |
| 0.7779        | 63.0  | 693  | 0.0004          | 8.6577 | 9.5337  |
| 0.7779        | 64.0  | 704  | 0.0003          | 8.6577 | 9.5337  |
| 0.7779        | 65.0  | 715  | 0.0004          | 8.6577 | 9.5337  |
| 0.7779        | 66.0  | 726  | 0.0002          | 8.6577 | 9.5337  |
| 0.7779        | 67.0  | 737  | 0.0002          | 8.6577 | 9.5337  |
| 0.7779        | 68.0  | 748  | 0.0003          | 8.6577 | 9.5337  |
| 0.7779        | 69.0  | 759  | 0.0007          | 8.6211 | 9.5337  |
| 0.7779        | 70.0  | 770  | 0.0006          | 8.6577 | 9.5337  |
| 0.7779        | 71.0  | 781  | 0.0001          | 8.6577 | 9.5337  |
| 0.7779        | 72.0  | 792  | 0.0001          | 8.6577 | 9.5337  |
| 0.7779        | 73.0  | 803  | 0.0010          | 8.6577 | 9.5337  |
| 0.7779        | 74.0  | 814  | 0.0002          | 8.6577 | 9.5337  |
| 0.7779        | 75.0  | 825  | 0.0005          | 8.6577 | 9.5337  |
| 0.7779        | 76.0  | 836  | 0.0005          | 8.6577 | 9.5337  |
| 0.7779        | 77.0  | 847  | 0.0006          | 8.6577 | 9.5337  |
| 0.7779        | 78.0  | 858  | 0.0003          | 8.6577 | 9.5337  |
| 0.7779        | 79.0  | 869  | 0.0001          | 8.6577 | 9.5337  |
| 0.7779        | 80.0  | 880  | 0.0001          | 8.6577 | 9.5337  |
| 0.7779        | 81.0  | 891  | 0.0001          | 8.6577 | 9.5337  |
| 0.7779        | 82.0  | 902  | 0.0001          | 8.6577 | 9.5337  |
| 0.7779        | 83.0  | 913  | 0.0002          | 8.6577 | 9.5337  |
| 0.7779        | 84.0  | 924  | 0.0005          | 8.6577 | 9.5337  |
| 0.7779        | 85.0  | 935  | 0.0003          | 8.6577 | 9.5337  |
| 0.7779        | 86.0  | 946  | 0.0000          | 8.6577 | 9.5337  |
| 0.7779        | 87.0  | 957  | 0.0001          | 8.6577 | 9.5337  |
| 0.7779        | 88.0  | 968  | 0.0042          | 8.653  | 9.5337  |
| 0.7779        | 89.0  | 979  | 0.0001          | 8.6577 | 9.5337  |
| 0.7779        | 90.0  | 990  | 0.0002          | 8.6355 | 9.5337  |
| 0.0387        | 91.0  | 1001 | 0.0001          | 8.6577 | 9.5337  |
| 0.0387        | 92.0  | 1012 | 0.0000          | 8.6577 | 9.5337  |
| 0.0387        | 93.0  | 1023 | 0.0000          | 8.6577 | 9.5337  |
| 0.0387        | 94.0  | 1034 | 0.0001          | 8.6577 | 9.5337  |
| 0.0387        | 95.0  | 1045 | 0.0002          | 8.591  | 9.5337  |
| 0.0387        | 96.0  | 1056 | 0.0003          | 8.6577 | 9.5337  |
| 0.0387        | 97.0  | 1067 | 0.0001          | 8.6577 | 9.5337  |
| 0.0387        | 98.0  | 1078 | 0.0000          | 8.6577 | 9.5337  |
| 0.0387        | 99.0  | 1089 | 0.0000          | 8.6577 | 9.5337  |
| 0.0387        | 100.0 | 1100 | 0.0000          | 8.6577 | 9.5337  |
| 0.0387        | 101.0 | 1111 | 0.0000          | 8.6577 | 9.5337  |
| 0.0387        | 102.0 | 1122 | 0.0000          | 8.6577 | 9.5337  |
| 0.0387        | 103.0 | 1133 | 0.0000          | 8.6577 | 9.5337  |
| 0.0387        | 104.0 | 1144 | 0.0000          | 8.6577 | 9.5337  |
| 0.0387        | 105.0 | 1155 | 0.0000          | 8.6577 | 9.5337  |
| 0.0387        | 106.0 | 1166 | 0.0000          | 8.6577 | 9.5337  |
| 0.0387        | 107.0 | 1177 | 0.0000          | 8.6577 | 9.5337  |
| 0.0387        | 108.0 | 1188 | 0.0000          | 8.6577 | 9.5337  |
| 0.0387        | 109.0 | 1199 | 0.0000          | 8.6577 | 9.5337  |
| 0.0387        | 110.0 | 1210 | 0.0000          | 8.6577 | 9.5337  |
| 0.0387        | 111.0 | 1221 | 0.0000          | 8.6577 | 9.5337  |
| 0.0387        | 112.0 | 1232 | 0.0000          | 8.6577 | 9.5337  |
| 0.0387        | 113.0 | 1243 | 0.0000          | 8.6577 | 9.5337  |
| 0.0387        | 114.0 | 1254 | 0.0000          | 8.6577 | 9.5337  |
| 0.0387        | 115.0 | 1265 | 0.0002          | 8.6036 | 9.5337  |
| 0.0387        | 116.0 | 1276 | 0.0001          | 8.6577 | 9.5337  |
| 0.0387        | 117.0 | 1287 | 0.0000          | 8.6577 | 9.5337  |
| 0.0387        | 118.0 | 1298 | 0.0000          | 8.6577 | 9.5337  |
| 0.0387        | 119.0 | 1309 | 0.0000          | 8.6577 | 9.5337  |
| 0.0387        | 120.0 | 1320 | 0.0012          | 8.5758 | 9.5337  |
| 0.0387        | 121.0 | 1331 | 0.0010          | 8.5758 | 9.5337  |
| 0.0387        | 122.0 | 1342 | 0.0003          | 8.6577 | 9.5337  |
| 0.0387        | 123.0 | 1353 | 0.0000          | 8.6577 | 9.5337  |
| 0.0387        | 124.0 | 1364 | 0.0000          | 8.6577 | 9.5337  |
| 0.0387        | 125.0 | 1375 | 0.0000          | 8.6577 | 9.5337  |
| 0.0387        | 126.0 | 1386 | 0.0000          | 8.6577 | 9.5337  |
| 0.0387        | 127.0 | 1397 | 0.0000          | 8.6577 | 9.5337  |
| 0.0387        | 128.0 | 1408 | 0.0000          | 8.6577 | 9.5337  |
| 0.0387        | 129.0 | 1419 | 0.0000          | 8.6577 | 9.5337  |
| 0.0387        | 130.0 | 1430 | 0.0000          | 8.6577 | 9.5337  |
| 0.0387        | 131.0 | 1441 | 0.0000          | 8.6577 | 9.5337  |
| 0.0387        | 132.0 | 1452 | 0.0000          | 8.6577 | 9.5337  |
| 0.0387        | 133.0 | 1463 | 0.0000          | 8.6577 | 9.5337  |
| 0.0387        | 134.0 | 1474 | 0.0000          | 8.6577 | 9.5337  |
| 0.0387        | 135.0 | 1485 | 0.0000          | 8.6577 | 9.5337  |
| 0.0387        | 136.0 | 1496 | 0.0000          | 8.6577 | 9.5337  |
| 0.0123        | 137.0 | 1507 | 0.0000          | 8.6577 | 9.5337  |
| 0.0123        | 138.0 | 1518 | 0.0000          | 8.6577 | 9.5337  |
| 0.0123        | 139.0 | 1529 | 0.0000          | 8.6577 | 9.5337  |
| 0.0123        | 140.0 | 1540 | 0.0000          | 8.6577 | 9.5337  |
| 0.0123        | 141.0 | 1551 | 0.0000          | 8.6577 | 9.5337  |
| 0.0123        | 142.0 | 1562 | 0.0000          | 8.6577 | 9.5337  |
| 0.0123        | 143.0 | 1573 | 0.0000          | 8.6577 | 9.5337  |
| 0.0123        | 144.0 | 1584 | 0.0000          | 8.6577 | 9.5337  |
| 0.0123        | 145.0 | 1595 | 0.0000          | 8.6577 | 9.5337  |
| 0.0123        | 146.0 | 1606 | 0.0000          | 8.6577 | 9.5337  |
| 0.0123        | 147.0 | 1617 | 0.0000          | 8.6577 | 9.5337  |
| 0.0123        | 148.0 | 1628 | 0.0000          | 8.6577 | 9.5337  |
| 0.0123        | 149.0 | 1639 | 0.0000          | 8.6577 | 9.5337  |
| 0.0123        | 150.0 | 1650 | 0.0000          | 8.6577 | 9.5337  |
| 0.0123        | 151.0 | 1661 | 0.0000          | 8.6577 | 9.5337  |
| 0.0123        | 152.0 | 1672 | 0.0000          | 8.6577 | 9.5337  |
| 0.0123        | 153.0 | 1683 | 0.0000          | 8.6577 | 9.5337  |
| 0.0123        | 154.0 | 1694 | 0.0000          | 8.6577 | 9.5337  |
| 0.0123        | 155.0 | 1705 | 0.0000          | 8.6577 | 9.5337  |
| 0.0123        | 156.0 | 1716 | 0.0000          | 8.6577 | 9.5337  |
| 0.0123        | 157.0 | 1727 | 0.0000          | 8.6577 | 9.5337  |
| 0.0123        | 158.0 | 1738 | 0.0000          | 8.6577 | 9.5337  |
| 0.0123        | 159.0 | 1749 | 0.0000          | 8.6577 | 9.5337  |
| 0.0123        | 160.0 | 1760 | 0.0000          | 8.6577 | 9.5337  |
| 0.0123        | 161.0 | 1771 | 0.0000          | 8.6577 | 9.5337  |
| 0.0123        | 162.0 | 1782 | 0.0000          | 8.6577 | 9.5337  |
| 0.0123        | 163.0 | 1793 | 0.0000          | 8.6577 | 9.5337  |
| 0.0123        | 164.0 | 1804 | 0.0000          | 8.6577 | 9.5337  |
| 0.0123        | 165.0 | 1815 | 0.0000          | 8.6577 | 9.5337  |
| 0.0123        | 166.0 | 1826 | 0.0000          | 8.6577 | 9.5337  |
| 0.0123        | 167.0 | 1837 | 0.0000          | 8.6577 | 9.5337  |
| 0.0123        | 168.0 | 1848 | 0.0000          | 8.6577 | 9.5337  |
| 0.0123        | 169.0 | 1859 | 0.0000          | 8.6577 | 9.5337  |
| 0.0123        | 170.0 | 1870 | 0.0000          | 8.6577 | 9.5337  |
| 0.0123        | 171.0 | 1881 | 0.0000          | 8.6577 | 9.5337  |
| 0.0123        | 172.0 | 1892 | 0.0000          | 8.6577 | 9.5337  |
| 0.0123        | 173.0 | 1903 | 0.0000          | 8.6577 | 9.5337  |
| 0.0123        | 174.0 | 1914 | 0.0000          | 8.6577 | 9.5337  |
| 0.0123        | 175.0 | 1925 | 0.0000          | 8.6577 | 9.5337  |
| 0.0123        | 176.0 | 1936 | 0.0000          | 8.6577 | 9.5337  |
| 0.0123        | 177.0 | 1947 | 0.0000          | 8.6577 | 9.5337  |
| 0.0123        | 178.0 | 1958 | 0.0000          | 8.6577 | 9.5337  |
| 0.0123        | 179.0 | 1969 | 0.0000          | 8.6577 | 9.5337  |
| 0.0123        | 180.0 | 1980 | 0.0000          | 8.6577 | 9.5337  |
| 0.0123        | 181.0 | 1991 | 0.0000          | 8.6577 | 9.5337  |
| 0.0053        | 182.0 | 2002 | 0.0000          | 8.6577 | 9.5337  |
| 0.0053        | 183.0 | 2013 | 0.0000          | 8.6577 | 9.5337  |
| 0.0053        | 184.0 | 2024 | 0.0000          | 8.6577 | 9.5337  |
| 0.0053        | 185.0 | 2035 | 0.0000          | 8.6577 | 9.5337  |
| 0.0053        | 186.0 | 2046 | 0.0000          | 8.6577 | 9.5337  |
| 0.0053        | 187.0 | 2057 | 0.0000          | 8.6577 | 9.5337  |
| 0.0053        | 188.0 | 2068 | 0.0000          | 8.6577 | 9.5337  |
| 0.0053        | 189.0 | 2079 | 0.0000          | 8.6577 | 9.5337  |
| 0.0053        | 190.0 | 2090 | 0.0000          | 8.6577 | 9.5337  |
| 0.0053        | 191.0 | 2101 | 0.0000          | 8.6577 | 9.5337  |
| 0.0053        | 192.0 | 2112 | 0.0000          | 8.6577 | 9.5337  |
| 0.0053        | 193.0 | 2123 | 0.0000          | 8.6577 | 9.5337  |
| 0.0053        | 194.0 | 2134 | 0.0000          | 8.6577 | 9.5337  |
| 0.0053        | 195.0 | 2145 | 0.0000          | 8.6577 | 9.5337  |
| 0.0053        | 196.0 | 2156 | 0.0000          | 8.6577 | 9.5337  |
| 0.0053        | 197.0 | 2167 | 0.0000          | 8.6577 | 9.5337  |
| 0.0053        | 198.0 | 2178 | 0.0000          | 8.6577 | 9.5337  |
| 0.0053        | 199.0 | 2189 | 0.0000          | 8.6577 | 9.5337  |
| 0.0053        | 200.0 | 2200 | 0.0000          | 8.6577 | 9.5337  |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0
