---
license: apache-2.0
base_model: google/t5-v1_1-large
tags:
- generated_from_trainer
model-index:
- name: SChem5Labels-google-t5-v1_1-large-intra_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. -->

# SChem5Labels-google-t5-v1_1-large-intra_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: 1.3184

## 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 |
|:-------------:|:-----:|:----:|:---------------:|
| 20.7337       | 1.0   | 25   | 23.6105         |
| 19.8181       | 2.0   | 50   | 21.7021         |
| 18.5121       | 3.0   | 75   | 18.6451         |
| 16.2008       | 4.0   | 100  | 12.8515         |
| 14.7585       | 5.0   | 125  | 10.1513         |
| 11.4985       | 6.0   | 150  | 9.3063          |
| 10.0012       | 7.0   | 175  | 9.0999          |
| 8.6447        | 8.0   | 200  | 8.8536          |
| 8.3766        | 9.0   | 225  | 8.7377          |
| 8.1231        | 10.0  | 250  | 8.6065          |
| 8.0504        | 11.0  | 275  | 8.4953          |
| 8.0051        | 12.0  | 300  | 8.3466          |
| 7.7615        | 13.0  | 325  | 8.1101          |
| 7.6344        | 14.0  | 350  | 7.8434          |
| 7.3869        | 15.0  | 375  | 7.6118          |
| 7.3158        | 16.0  | 400  | 7.4364          |
| 7.1667        | 17.0  | 425  | 7.3245          |
| 6.988         | 18.0  | 450  | 7.2732          |
| 7.0234        | 19.0  | 475  | 7.2125          |
| 6.9602        | 20.0  | 500  | 7.1699          |
| 6.8268        | 21.0  | 525  | 7.1251          |
| 6.8999        | 22.0  | 550  | 7.0695          |
| 6.3358        | 23.0  | 575  | 0.6967          |
| 0.86          | 24.0  | 600  | 0.6708          |
| 0.7148        | 25.0  | 625  | 0.6347          |
| 0.674         | 26.0  | 650  | 0.6297          |
| 0.6683        | 27.0  | 675  | 0.6234          |
| 0.6711        | 28.0  | 700  | 0.6214          |
| 0.6773        | 29.0  | 725  | 0.6170          |
| 0.6596        | 30.0  | 750  | 0.6162          |
| 0.6812        | 31.0  | 775  | 0.6207          |
| 0.6813        | 32.0  | 800  | 0.6121          |
| 0.6655        | 33.0  | 825  | 0.6147          |
| 0.653         | 34.0  | 850  | 0.6112          |
| 0.651         | 35.0  | 875  | 0.6082          |
| 0.6659        | 36.0  | 900  | 0.6075          |
| 0.6639        | 37.0  | 925  | 0.6023          |
| 0.6529        | 38.0  | 950  | 0.5998          |
| 0.6434        | 39.0  | 975  | 0.6023          |
| 0.645         | 40.0  | 1000 | 0.5976          |
| 0.64          | 41.0  | 1025 | 0.5987          |
| 0.6423        | 42.0  | 1050 | 0.5971          |
| 0.6439        | 43.0  | 1075 | 0.5940          |
| 0.6472        | 44.0  | 1100 | 0.5946          |
| 0.6459        | 45.0  | 1125 | 0.5965          |
| 0.6229        | 46.0  | 1150 | 0.5940          |
| 0.6414        | 47.0  | 1175 | 0.6111          |
| 0.6215        | 48.0  | 1200 | 0.5910          |
| 0.6375        | 49.0  | 1225 | 0.5928          |
| 0.6324        | 50.0  | 1250 | 0.6103          |
| 0.6212        | 51.0  | 1275 | 0.6075          |
| 0.6406        | 52.0  | 1300 | 0.5869          |
| 0.631         | 53.0  | 1325 | 0.5866          |
| 0.6227        | 54.0  | 1350 | 0.5833          |
| 0.6255        | 55.0  | 1375 | 0.5837          |
| 0.633         | 56.0  | 1400 | 0.5833          |
| 0.6224        | 57.0  | 1425 | 0.5822          |
| 0.628         | 58.0  | 1450 | 0.5858          |
| 0.62          | 59.0  | 1475 | 0.5827          |
| 0.6211        | 60.0  | 1500 | 0.5834          |
| 0.6236        | 61.0  | 1525 | 0.5794          |
| 0.6136        | 62.0  | 1550 | 0.5820          |
| 0.6132        | 63.0  | 1575 | 0.5800          |
| 0.6098        | 64.0  | 1600 | 0.5788          |
| 0.6167        | 65.0  | 1625 | 0.5785          |
| 0.6271        | 66.0  | 1650 | 0.5794          |
| 0.615         | 67.0  | 1675 | 0.5764          |
| 0.6143        | 68.0  | 1700 | 0.5789          |
| 0.6085        | 69.0  | 1725 | 0.5756          |
| 0.611         | 70.0  | 1750 | 0.5740          |
| 0.6161        | 71.0  | 1775 | 0.5730          |
| 0.5999        | 72.0  | 1800 | 0.5738          |
| 0.6194        | 73.0  | 1825 | 0.5753          |
| 0.6221        | 74.0  | 1850 | 0.5731          |
| 0.6061        | 75.0  | 1875 | 0.5738          |
| 0.6038        | 76.0  | 1900 | 0.5745          |


### Framework versions

- Transformers 4.34.0
- Pytorch 2.1.0+cu121
- Datasets 2.6.1
- Tokenizers 0.14.1