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-intra_model-shuffle
  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-intra_model-shuffle

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: nan

## 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 |
|:-------------:|:-----:|:----:|:---------------:|
| 26.6182       | 1.0   | 44   | 31.1790         |
| 25.1664       | 2.0   | 88   | 25.9630         |
| 19.7407       | 3.0   | 132  | 17.5483         |
| 17.0241       | 4.0   | 176  | 15.7951         |
| 14.1013       | 5.0   | 220  | 13.6385         |
| 12.6633       | 6.0   | 264  | 12.1849         |
| 11.7434       | 7.0   | 308  | 11.5528         |
| 10.4633       | 8.0   | 352  | 10.7603         |
| 10.0142       | 9.0   | 396  | 9.7449          |
| 9.4309        | 10.0  | 440  | 9.4058          |
| 9.4721        | 11.0  | 484  | 9.2254          |
| 8.9759        | 12.0  | 528  | 9.0880          |
| 8.9786        | 13.0  | 572  | 9.0002          |
| 8.8538        | 14.0  | 616  | 8.9090          |
| 8.9413        | 15.0  | 660  | 8.8425          |
| 8.7639        | 16.0  | 704  | 8.7726          |
| 8.7977        | 17.0  | 748  | 8.6950          |
| 8.5634        | 18.0  | 792  | 8.6210          |
| 8.5154        | 19.0  | 836  | 8.5771          |
| 8.3299        | 20.0  | 880  | 8.5047          |
| 8.2768        | 21.0  | 924  | 8.4541          |
| 8.2174        | 22.0  | 968  | 8.3483          |
| 4.2638        | 23.0  | 1012 | 3.7590          |
| 3.9317        | 24.0  | 1056 | 3.7476          |
| 3.8703        | 25.0  | 1100 | 3.7268          |
| 3.8648        | 26.0  | 1144 | 3.7015          |
| 3.7132        | 27.0  | 1188 | 3.6620          |
| 3.7982        | 28.0  | 1232 | 3.6444          |
| 3.7453        | 29.0  | 1276 | 3.6329          |
| 3.6892        | 30.0  | 1320 | 3.5919          |
| 2.7956        | 31.0  | 1364 | 2.0820          |
| 1.2507        | 32.0  | 1408 | 1.0523          |
| 1.1008        | 33.0  | 1452 | 1.0461          |
| 1.1059        | 34.0  | 1496 | 1.0464          |
| 1.1015        | 35.0  | 1540 | 1.0460          |
| 1.079         | 36.0  | 1584 | 1.0446          |
| 1.0946        | 37.0  | 1628 | 1.0438          |
| 1.0985        | 38.0  | 1672 | 1.0461          |
| 1.0817        | 39.0  | 1716 | 1.0419          |
| 1.0723        | 40.0  | 1760 | 1.0417          |
| 1.0867        | 41.0  | 1804 | 1.0411          |
| 1.0654        | 42.0  | 1848 | 1.0415          |
| 1.0739        | 43.0  | 1892 | 1.0385          |
| 1.0643        | 44.0  | 1936 | 1.0395          |
| 1.0585        | 45.0  | 1980 | 1.0359          |
| 1.0784        | 46.0  | 2024 | 1.0375          |
| 1.0831        | 47.0  | 2068 | 1.0349          |
| 1.0652        | 48.0  | 2112 | 1.0355          |
| 1.0687        | 49.0  | 2156 | 1.0333          |
| 1.0717        | 50.0  | 2200 | 1.0350          |
| 1.0576        | 51.0  | 2244 | 1.0339          |
| 1.0666        | 52.0  | 2288 | 1.0339          |
| 1.0648        | 53.0  | 2332 | 1.0334          |
| 1.0624        | 54.0  | 2376 | 1.0323          |
| 1.0745        | 55.0  | 2420 | 1.0321          |
| 1.0542        | 56.0  | 2464 | 1.0339          |
| 1.054         | 57.0  | 2508 | 1.0320          |
| 1.0866        | 58.0  | 2552 | 1.0294          |
| 1.0704        | 59.0  | 2596 | 1.0315          |
| 1.0706        | 60.0  | 2640 | 1.0303          |
| 1.0464        | 61.0  | 2684 | 1.0312          |
| 1.0614        | 62.0  | 2728 | 1.0288          |
| 1.0645        | 63.0  | 2772 | 1.0302          |
| 1.057         | 64.0  | 2816 | 1.0318          |
| 1.0586        | 65.0  | 2860 | 1.0285          |
| 1.0724        | 66.0  | 2904 | 1.0300          |
| 1.0539        | 67.0  | 2948 | 1.0271          |
| 1.0536        | 68.0  | 2992 | 1.0292          |
| 1.0595        | 69.0  | 3036 | 1.0271          |
| 1.0504        | 70.0  | 3080 | 1.0296          |
| 1.0673        | 71.0  | 3124 | 1.0264          |
| 1.0548        | 72.0  | 3168 | 1.0277          |
| 1.0519        | 73.0  | 3212 | 1.0280          |
| 1.0519        | 74.0  | 3256 | 1.0260          |
| 1.0497        | 75.0  | 3300 | 1.0286          |
| 1.0551        | 76.0  | 3344 | 1.0253          |
| 1.0605        | 77.0  | 3388 | 1.0250          |
| 1.0495        | 78.0  | 3432 | 1.0250          |
| 1.0546        | 79.0  | 3476 | 1.0263          |
| 1.0615        | 80.0  | 3520 | 1.0255          |
| 1.0603        | 81.0  | 3564 | 1.0238          |
| 1.0374        | 82.0  | 3608 | 1.0244          |
| 1.0418        | 83.0  | 3652 | 1.0252          |
| 1.0603        | 84.0  | 3696 | 1.0241          |
| 1.0459        | 85.0  | 3740 | 1.0233          |
| 1.0598        | 86.0  | 3784 | 1.0222          |
| 1.0589        | 87.0  | 3828 | 1.0232          |
| 1.0415        | 88.0  | 3872 | 1.0223          |
| 1.0521        | 89.0  | 3916 | 1.0202          |
| 1.0443        | 90.0  | 3960 | 1.0198          |
| 1.0629        | 91.0  | 4004 | 1.0200          |
| 1.0616        | 92.0  | 4048 | 1.0194          |
| 1.059         | 93.0  | 4092 | 1.0189          |
| 1.036         | 94.0  | 4136 | 1.0226          |
| 1.0578        | 95.0  | 4180 | 1.0194          |
| 1.0463        | 96.0  | 4224 | 1.0180          |
| 1.0586        | 97.0  | 4268 | 1.0169          |
| 1.0541        | 98.0  | 4312 | 1.0182          |
| 1.052         | 99.0  | 4356 | 1.0154          |
| 1.0443        | 100.0 | 4400 | 1.0160          |
| 1.0573        | 101.0 | 4444 | 1.0131          |
| 1.0423        | 102.0 | 4488 | 1.0151          |
| 1.0532        | 103.0 | 4532 | 1.0127          |
| 1.0527        | 104.0 | 4576 | 1.0117          |
| 1.0387        | 105.0 | 4620 | 1.0120          |
| 1.0514        | 106.0 | 4664 | 1.0101          |
| 1.0436        | 107.0 | 4708 | 1.0110          |
| 1.0377        | 108.0 | 4752 | 1.0099          |
| 1.044         | 109.0 | 4796 | 1.0242          |
| 1.0399        | 110.0 | 4840 | 1.0139          |
| 1.0568        | 111.0 | 4884 | 1.0099          |
| 1.079         | 112.0 | 4928 | 1.0127          |
| 1.0611        | 113.0 | 4972 | 1.0269          |
| 1.0947        | 114.0 | 5016 | 1.0337          |
| 1.0635        | 115.0 | 5060 | 1.0312          |
| 1.0732        | 116.0 | 5104 | 1.0279          |


### Framework versions

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