---
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-model_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-model_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: 0.8369

## 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 |
|:-------------:|:-----:|:----:|:---------------:|
| 19.8258       | 1.0   | 25   | 23.6474         |
| 19.0315       | 2.0   | 50   | 22.0370         |
| 18.08         | 3.0   | 75   | 19.1087         |
| 16.4078       | 4.0   | 100  | 11.6693         |
| 14.5372       | 5.0   | 125  | 10.0089         |
| 12.1759       | 6.0   | 150  | 9.5651          |
| 10.8249       | 7.0   | 175  | 9.2475          |
| 9.4751        | 8.0   | 200  | 8.9311          |
| 8.801         | 9.0   | 225  | 8.6771          |
| 8.1126        | 10.0  | 250  | 8.5237          |
| 7.9399        | 11.0  | 275  | 8.4068          |
| 7.9146        | 12.0  | 300  | 8.3324          |
| 7.9766        | 13.0  | 325  | 8.2182          |
| 7.6203        | 14.0  | 350  | 8.0454          |
| 7.5088        | 15.0  | 375  | 7.7369          |
| 7.2191        | 16.0  | 400  | 7.4618          |
| 7.0805        | 17.0  | 425  | 7.2855          |
| 6.8971        | 18.0  | 450  | 7.1672          |
| 6.8954        | 19.0  | 475  | 7.0791          |
| 6.7074        | 20.0  | 500  | 7.0220          |
| 6.6851        | 21.0  | 525  | 6.9700          |
| 6.6409        | 22.0  | 550  | 6.9230          |
| 6.5565        | 23.0  | 575  | 6.8672          |
| 6.4106        | 24.0  | 600  | 6.8143          |
| 5.2007        | 25.0  | 625  | 2.4787          |
| 0.9209        | 26.0  | 650  | 0.7582          |
| 0.8058        | 27.0  | 675  | 0.7280          |
| 0.7899        | 28.0  | 700  | 0.7278          |
| 0.7875        | 29.0  | 725  | 0.7233          |
| 0.7813        | 30.0  | 750  | 0.7216          |
| 0.7621        | 31.0  | 775  | 0.7209          |
| 0.7893        | 32.0  | 800  | 0.7156          |
| 0.7727        | 33.0  | 825  | 0.7116          |
| 0.7562        | 34.0  | 850  | 0.7143          |
| 0.7639        | 35.0  | 875  | 0.7136          |
| 0.7553        | 36.0  | 900  | 0.7087          |
| 0.7382        | 37.0  | 925  | 0.7072          |
| 0.7361        | 38.0  | 950  | 0.7106          |
| 0.7469        | 39.0  | 975  | 0.7059          |
| 0.7516        | 40.0  | 1000 | 0.7074          |
| 0.7478        | 41.0  | 1025 | 0.7051          |
| 0.7367        | 42.0  | 1050 | 0.7096          |
| 0.7417        | 43.0  | 1075 | 0.7057          |
| 0.7434        | 44.0  | 1100 | 0.7056          |
| 0.7433        | 45.0  | 1125 | 0.7022          |
| 0.7538        | 46.0  | 1150 | 0.7024          |
| 0.7246        | 47.0  | 1175 | 0.7004          |
| 0.7418        | 48.0  | 1200 | 0.7014          |
| 0.7469        | 49.0  | 1225 | 0.7038          |
| 0.7184        | 50.0  | 1250 | 0.6997          |
| 0.7459        | 51.0  | 1275 | 0.6998          |
| 0.716         | 52.0  | 1300 | 0.7008          |
| 0.7269        | 53.0  | 1325 | 0.7015          |
| 0.7354        | 54.0  | 1350 | 0.6979          |
| 0.7209        | 55.0  | 1375 | 0.6976          |
| 0.728         | 56.0  | 1400 | 0.6948          |
| 0.7201        | 57.0  | 1425 | 0.6986          |
| 0.7228        | 58.0  | 1450 | 0.6957          |
| 0.7254        | 59.0  | 1475 | 0.6996          |
| 0.7252        | 60.0  | 1500 | 0.6961          |
| 0.7116        | 61.0  | 1525 | 0.6987          |


### Framework versions

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