---
license: apache-2.0
base_model: google/t5-v1_1-large
tags:
- generated_from_trainer
model-index:
- name: SChem5Labels-google-t5-v1_1-large-inter_model-shuffle-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-inter_model-shuffle-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: 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 |
|:-------------:|:-----:|:----:|:---------------:|
| 19.9516       | 1.0   | 25   | 23.6924         |
| 18.985        | 2.0   | 50   | 21.9715         |
| 18.5733       | 3.0   | 75   | 19.0631         |
| 16.456        | 4.0   | 100  | 14.6944         |
| 14.6058       | 5.0   | 125  | 10.3972         |
| 11.384        | 6.0   | 150  | 8.9604          |
| 10.1534       | 7.0   | 175  | 8.6228          |
| 8.6467        | 8.0   | 200  | 8.4688          |
| 8.2161        | 9.0   | 225  | 8.3154          |
| 7.9229        | 10.0  | 250  | 8.2324          |
| 7.8179        | 11.0  | 275  | 8.1809          |
| 7.7843        | 12.0  | 300  | 8.0948          |
| 7.5714        | 13.0  | 325  | 7.9681          |
| 7.2487        | 14.0  | 350  | 7.7352          |
| 7.2237        | 15.0  | 375  | 7.4691          |
| 6.9821        | 16.0  | 400  | 7.2523          |
| 6.8667        | 17.0  | 425  | 7.1151          |
| 6.8551        | 18.0  | 450  | 7.0423          |
| 6.7468        | 19.0  | 475  | 6.9926          |
| 6.6918        | 20.0  | 500  | 6.9466          |
| 6.4912        | 21.0  | 525  | 6.9125          |
| 6.5704        | 22.0  | 550  | 6.8707          |
| 6.4854        | 23.0  | 575  | 6.8123          |
| 3.9521        | 24.0  | 600  | 1.5605          |
| 1.16          | 25.0  | 625  | 1.0195          |
| 1.0643        | 26.0  | 650  | 1.0007          |
| 1.0417        | 27.0  | 675  | 1.0069          |
| 1.04          | 28.0  | 700  | 0.9974          |
| 1.0347        | 29.0  | 725  | 0.9974          |
| 1.0375        | 30.0  | 750  | 1.0006          |
| 1.0382        | 31.0  | 775  | 0.9958          |
| 1.0347        | 32.0  | 800  | 0.9999          |
| 1.0198        | 33.0  | 825  | 1.0013          |
| 1.0092        | 34.0  | 850  | 1.0044          |
| 1.0376        | 35.0  | 875  | 1.0045          |
| 1.0245        | 36.0  | 900  | 0.9974          |


### Framework versions

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