generated_from_trainer base_model:google/t5-v1_1-large license:apache-2.0 region:us
---
license: apache-2.0
base_model: google/t5-v1_1-large
tags:
- generated_from_trainer
model-index:
- name: Sentiment-google-t5-v1_1-large-inter_model-frequency-human_annots_str
  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. -->

# Sentiment-google-t5-v1_1-large-inter_model-frequency-human_annots_str

This model is a fine-tuned version of [google/t5-v1_1-large](https://huggingface.co/google/t5-v1_1-large) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.2676

## 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: 0.0001
- train_batch_size: 128
- eval_batch_size: 128
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 200

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 20.8675       | 1.0   | 44   | 24.9691         |
| 18.2491       | 2.0   | 88   | 16.9536         |
| 13.3557       | 3.0   | 132  | 11.4063         |
| 11.0809       | 4.0   | 176  | 10.9529         |
| 10.1527       | 5.0   | 220  | 10.7258         |
| 9.9235        | 6.0   | 264  | 10.5299         |
| 9.8499        | 7.0   | 308  | 10.3942         |
| 9.5638        | 8.0   | 352  | 10.0279         |
| 9.0218        | 9.0   | 396  | 9.4463          |
| 8.5704        | 10.0  | 440  | 9.0452          |
| 8.3982        | 11.0  | 484  | 8.8619          |
| 8.3396        | 12.0  | 528  | 8.7363          |
| 7.0951        | 13.0  | 572  | 1.3757          |
| 1.1349        | 14.0  | 616  | 1.0516          |
| 1.0735        | 15.0  | 660  | 1.0456          |
| 1.0787        | 16.0  | 704  | 1.0342          |
| 1.0796        | 17.0  | 748  | 1.0342          |
| 1.0476        | 18.0  | 792  | 1.0318          |
| 1.0566        | 19.0  | 836  | 1.0311          |
| 1.0472        | 20.0  | 880  | 1.0247          |
| 1.0401        | 21.0  | 924  | 1.0201          |
| 1.0725        | 22.0  | 968  | 1.0159          |
| 1.0447        | 23.0  | 1012 | 1.0180          |
| 1.0477        | 24.0  | 1056 | 1.0121          |
| 1.0357        | 25.0  | 1100 | 1.0109          |
| 1.0333        | 26.0  | 1144 | 1.0096          |
| 1.0282        | 27.0  | 1188 | 1.0078          |
| 1.0206        | 28.0  | 1232 | 1.0100          |
| 1.0241        | 29.0  | 1276 | 1.0081          |
| 1.023         | 30.0  | 1320 | 1.0053          |
| 0.9993        | 31.0  | 1364 | 1.0073          |
| 1.0104        | 32.0  | 1408 | 1.0079          |
| 1.0176        | 33.0  | 1452 | 1.0014          |
| 1.0157        | 34.0  | 1496 | 0.9977          |
| 1.0204        | 35.0  | 1540 | 0.9960          |
| 1.0174        | 36.0  | 1584 | 0.9967          |
| 1.0252        | 37.0  | 1628 | 0.9949          |
| 1.0076        | 38.0  | 1672 | 0.9913          |
| 1.0137        | 39.0  | 1716 | 0.9874          |
| 1.0151        | 40.0  | 1760 | 0.9856          |
| 0.9907        | 41.0  | 1804 | 0.9843          |
| 1.0147        | 42.0  | 1848 | 0.9803          |
| 1.001         | 43.0  | 1892 | 0.9777          |
| 1.0009        | 44.0  | 1936 | 0.9735          |
| 0.9881        | 45.0  | 1980 | 0.9731          |
| 0.9973        | 46.0  | 2024 | 0.9761          |
| 0.9982        | 47.0  | 2068 | 0.9888          |
| 0.9826        | 48.0  | 2112 | 1.0006          |
| 0.9739        | 49.0  | 2156 | 0.9766          |
| 0.9659        | 50.0  | 2200 | 0.9525          |
| 0.9534        | 51.0  | 2244 | 0.9400          |
| 0.959         | 52.0  | 2288 | 0.9553          |
| 0.9492        | 53.0  | 2332 | 0.9308          |
| 0.9629        | 54.0  | 2376 | 0.9325          |
| 0.9532        | 55.0  | 2420 | 0.9288          |
| 0.9586        | 56.0  | 2464 | 0.9233          |
| 0.9511        | 57.0  | 2508 | 0.9228          |
| 0.9456        | 58.0  | 2552 | 0.9178          |
| 0.937         | 59.0  | 2596 | 0.9140          |
| 0.9415        | 60.0  | 2640 | 0.9332          |
| 0.9364        | 61.0  | 2684 | 0.9073          |
| 0.9304        | 62.0  | 2728 | 0.9112          |
| 0.9418        | 63.0  | 2772 | 0.9073          |
| 0.9423        | 64.0  | 2816 | 0.9079          |
| 0.9277        | 65.0  | 2860 | 0.9062          |
| 0.9274        | 66.0  | 2904 | 0.8999          |
| 0.9266        | 67.0  | 2948 | 0.8971          |
| 0.9231        | 68.0  | 2992 | 0.9003          |
| 0.9174        | 69.0  | 3036 | 0.8994          |
| 0.9036        | 70.0  | 3080 | 0.8986          |
| 0.9112        | 71.0  | 3124 | 0.8925          |
| 0.8929        | 72.0  | 3168 | 0.8866          |
| 0.9069        | 73.0  | 3212 | 0.8840          |
| 0.8922        | 74.0  | 3256 | 0.8818          |
| 0.9079        | 75.0  | 3300 | 0.8821          |
| 0.8941        | 76.0  | 3344 | 0.8780          |
| 0.8952        | 77.0  | 3388 | 0.8824          |
| 0.8881        | 78.0  | 3432 | 0.8724          |
| 0.884         | 79.0  | 3476 | 0.8684          |
| 0.8761        | 80.0  | 3520 | 0.8715          |
| 0.8952        | 81.0  | 3564 | 0.8706          |
| 0.8871        | 82.0  | 3608 | 0.8654          |
| 0.8772        | 83.0  | 3652 | 0.8583          |
| 0.8745        | 84.0  | 3696 | 0.8570          |
| 0.8683        | 85.0  | 3740 | 0.8490          |
| 0.8698        | 86.0  | 3784 | 0.8500          |
| 0.8562        | 87.0  | 3828 | 0.8469          |
| 0.8636        | 88.0  | 3872 | 0.8465          |
| 0.8669        | 89.0  | 3916 | 0.8359          |
| 0.8422        | 90.0  | 3960 | 0.8418          |
| 0.8568        | 91.0  | 4004 | 0.8332          |
| 0.8628        | 92.0  | 4048 | 0.8338          |
| 0.8599        | 93.0  | 4092 | 0.8302          |
| 0.8471        | 94.0  | 4136 | 0.8235          |
| 0.8432        | 95.0  | 4180 | 0.8202          |
| 0.8389        | 96.0  | 4224 | 0.8159          |
| 0.8347        | 97.0  | 4268 | 0.8218          |
| 0.8353        | 98.0  | 4312 | 0.8141          |
| 0.8172        | 99.0  | 4356 | 0.8176          |
| 0.8303        | 100.0 | 4400 | 0.8078          |
| 0.8317        | 101.0 | 4444 | 0.8077          |
| 0.8203        | 102.0 | 4488 | 0.8103          |
| 0.8224        | 103.0 | 4532 | 0.8076          |
| 0.8174        | 104.0 | 4576 | 0.8023          |
| 0.8242        | 105.0 | 4620 | 0.7897          |
| 0.809         | 106.0 | 4664 | 0.7935          |
| 0.8014        | 107.0 | 4708 | 0.7881          |
| 0.817         | 108.0 | 4752 | 0.7815          |
| 0.7988        | 109.0 | 4796 | 0.7861          |
| 0.8003        | 110.0 | 4840 | 0.7716          |
| 0.7991        | 111.0 | 4884 | 0.7836          |
| 0.7851        | 112.0 | 4928 | 0.7722          |
| 0.7884        | 113.0 | 4972 | 0.7716          |
| 0.7831        | 114.0 | 5016 | 0.7643          |
| 0.7849        | 115.0 | 5060 | 0.7767          |
| 0.7846        | 116.0 | 5104 | 0.7602          |
| 0.7887        | 117.0 | 5148 | 0.7511          |
| 0.7683        | 118.0 | 5192 | 0.7480          |
| 0.7856        | 119.0 | 5236 | 0.7532          |
| 0.766         | 120.0 | 5280 | 0.7511          |
| 0.7663        | 121.0 | 5324 | 0.7490          |
| 0.7456        | 122.0 | 5368 | 0.7460          |
| 0.7672        | 123.0 | 5412 | 0.7464          |
| 0.7553        | 124.0 | 5456 | 0.7324          |
| 0.7543        | 125.0 | 5500 | 0.7296          |
| 0.7465        | 126.0 | 5544 | 0.7431          |
| 0.7525        | 127.0 | 5588 | 0.7310          |
| 0.7438        | 128.0 | 5632 | 0.7333          |
| 0.7521        | 129.0 | 5676 | 0.7218          |
| 0.7501        | 130.0 | 5720 | 0.7170          |
| 0.7485        | 131.0 | 5764 | 0.7214          |
| 0.7512        | 132.0 | 5808 | 0.7235          |
| 0.7554        | 133.0 | 5852 | 0.7140          |
| 0.7349        | 134.0 | 5896 | 0.7062          |
| 0.7542        | 135.0 | 5940 | 0.7095          |
| 0.7303        | 136.0 | 5984 | 0.7111          |
| 0.7163        | 137.0 | 6028 | 0.7004          |
| 0.7204        | 138.0 | 6072 | 0.7045          |
| 0.7091        | 139.0 | 6116 | 0.6918          |
| 0.719         | 140.0 | 6160 | 0.6976          |
| 0.726         | 141.0 | 6204 | 0.6885          |
| 0.7079        | 142.0 | 6248 | 0.6896          |
| 0.7043        | 143.0 | 6292 | 0.6966          |
| 0.7078        | 144.0 | 6336 | 0.6833          |
| 0.711         | 145.0 | 6380 | 0.6839          |
| 0.7014        | 146.0 | 6424 | 0.6685          |
| 0.7026        | 147.0 | 6468 | 0.6752          |
| 0.6927        | 148.0 | 6512 | 0.6802          |
| 0.6899        | 149.0 | 6556 | 0.6747          |
| 0.7059        | 150.0 | 6600 | 0.6733          |
| 0.6855        | 151.0 | 6644 | 0.6551          |
| 0.694         | 152.0 | 6688 | 0.6590          |
| 0.6896        | 153.0 | 6732 | 0.6568          |
| 0.6758        | 154.0 | 6776 | 0.6595          |
| 0.7058        | 155.0 | 6820 | 0.6506          |
| 0.6761        | 156.0 | 6864 | 0.6586          |
| 0.6837        | 157.0 | 6908 | 0.6526          |
| 0.6736        | 158.0 | 6952 | 0.6526          |
| 0.6738        | 159.0 | 6996 | 0.6434          |
| 0.685         | 160.0 | 7040 | 0.6382          |
| 0.664         | 161.0 | 7084 | 0.6374          |
| 0.6878        | 162.0 | 7128 | 0.6322          |
| 0.6552        | 163.0 | 7172 | 0.6338          |
| 0.6796        | 164.0 | 7216 | 0.6453          |
| 0.6712        | 165.0 | 7260 | 0.6284          |
| 0.6683        | 166.0 | 7304 | 0.6249          |
| 0.6577        | 167.0 | 7348 | 0.6359          |
| 0.6462        | 168.0 | 7392 | 0.6193          |
| 0.66          | 169.0 | 7436 | 0.6138          |
| 0.6476        | 170.0 | 7480 | 0.6224          |
| 0.6444        | 171.0 | 7524 | 0.6195          |
| 0.6478        | 172.0 | 7568 | 0.6136          |
| 0.6332        | 173.0 | 7612 | 0.5981          |
| 0.6456        | 174.0 | 7656 | 0.6004          |
| 0.6302        | 175.0 | 7700 | 0.6060          |
| 0.6337        | 176.0 | 7744 | 0.6024          |
| 0.6282        | 177.0 | 7788 | 0.5936          |
| 0.616         | 178.0 | 7832 | 0.5942          |
| 0.6324        | 179.0 | 7876 | 0.6038          |
| 0.6331        | 180.0 | 7920 | 0.5939          |
| 0.627         | 181.0 | 7964 | 0.5881          |
| 0.6313        | 182.0 | 8008 | 0.5874          |
| 0.626         | 183.0 | 8052 | 0.5868          |
| 0.6215        | 184.0 | 8096 | 0.5789          |
| 0.6138        | 185.0 | 8140 | 0.5830          |
| 0.6235        | 186.0 | 8184 | 0.5900          |
| 0.61          | 187.0 | 8228 | 0.5920          |
| 0.6218        | 188.0 | 8272 | 0.5830          |
| 0.6265        | 189.0 | 8316 | 0.5706          |
| 0.6126        | 190.0 | 8360 | 0.5776          |
| 0.608         | 191.0 | 8404 | 0.5738          |
| 0.6143        | 192.0 | 8448 | 0.5737          |
| 0.6065        | 193.0 | 8492 | 0.5714          |
| 0.6213        | 194.0 | 8536 | 0.5657          |
| 0.6004        | 195.0 | 8580 | 0.5660          |
| 0.6229        | 196.0 | 8624 | 0.5646          |
| 0.6073        | 197.0 | 8668 | 0.5704          |
| 0.6048        | 198.0 | 8712 | 0.5696          |
| 0.6008        | 199.0 | 8756 | 0.5619          |
| 0.6157        | 200.0 | 8800 | 0.5597          |


### Framework versions

- Transformers 4.34.0
- Pytorch 2.1.0+cu121
- Datasets 2.14.5
- Tokenizers 0.14.1
