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: SChem5Labels-google-t5-v1_1-large-intra_model-dataset-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-dataset-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: 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 |
|:-------------:|:-----:|:----:|:---------------:|
| 20.6291       | 1.0   | 25   | 25.1686         |
| 19.5807       | 2.0   | 50   | 23.6946         |
| 18.3885       | 3.0   | 75   | 16.4506         |
| 15.6621       | 4.0   | 100  | 10.3654         |
| 14.1536       | 5.0   | 125  | 9.6059          |
| 11.1395       | 6.0   | 150  | 9.4016          |
| 10.234        | 7.0   | 175  | 9.1651          |
| 8.6134        | 8.0   | 200  | 8.8517          |
| 8.4527        | 9.0   | 225  | 8.7267          |
| 8.1685        | 10.0  | 250  | 8.6661          |
| 8.1419        | 11.0  | 275  | 8.5700          |
| 8.1851        | 12.0  | 300  | 8.4129          |
| 7.9855        | 13.0  | 325  | 8.1392          |
| 7.5843        | 14.0  | 350  | 7.8676          |
| 7.4604        | 15.0  | 375  | 7.6409          |
| 7.2433        | 16.0  | 400  | 7.4793          |
| 7.1782        | 17.0  | 425  | 7.3690          |
| 6.9756        | 18.0  | 450  | 7.2904          |
| 6.8602        | 19.0  | 475  | 7.2253          |
| 6.9456        | 20.0  | 500  | 7.1670          |
| 6.5134        | 21.0  | 525  | 0.6126          |
| 0.8013        | 22.0  | 550  | 0.5889          |
| 0.6372        | 23.0  | 575  | 0.5655          |
| 0.6054        | 24.0  | 600  | 0.5584          |
| 0.6018        | 25.0  | 625  | 0.5609          |
| 0.5884        | 26.0  | 650  | 0.5572          |
| 0.5887        | 27.0  | 675  | 0.5585          |
| 0.5919        | 28.0  | 700  | 0.5575          |
| 0.5908        | 29.0  | 725  | 0.5570          |
| 0.5859        | 30.0  | 750  | 0.5510          |
| 0.6028        | 31.0  | 775  | 0.5558          |
| 0.594         | 32.0  | 800  | 0.5491          |
| 0.5834        | 33.0  | 825  | 0.5556          |
| 0.5849        | 34.0  | 850  | 0.5515          |
| 0.5791        | 35.0  | 875  | 0.5519          |
| 0.5863        | 36.0  | 900  | 0.5553          |
| 0.5897        | 37.0  | 925  | 0.5486          |
| 0.582         | 38.0  | 950  | 0.5555          |
| 0.579         | 39.0  | 975  | 0.5519          |
| 0.5816        | 40.0  | 1000 | 0.5530          |
| 0.5822        | 41.0  | 1025 | 0.5483          |
| 0.5838        | 42.0  | 1050 | 0.5548          |
| 0.5767        | 43.0  | 1075 | 0.5479          |
| 0.5757        | 44.0  | 1100 | 0.5498          |
| 0.5911        | 45.0  | 1125 | 0.5515          |
| 0.5665        | 46.0  | 1150 | 0.5556          |
| 0.5773        | 47.0  | 1175 | 0.5518          |
| 0.5727        | 48.0  | 1200 | 0.5499          |


### Framework versions

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