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-inter_model-dataset-frequency-model_annots_str
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# SChem5Labels-google-t5-v1_1-large-inter_model-dataset-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: 0.8911

## 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 |
|:-------------:|:-----:|:----:|:---------------:|
| 19.7803       | 1.0   | 25   | 23.9207         |
| 18.7939       | 2.0   | 50   | 19.6774         |
| 17.9347       | 3.0   | 75   | 14.1935         |
| 14.9562       | 4.0   | 100  | 11.5018         |
| 12.9185       | 5.0   | 125  | 9.7946          |
| 11.0104       | 6.0   | 150  | 9.0519          |
| 10.1946       | 7.0   | 175  | 8.9336          |
| 8.6775        | 8.0   | 200  | 8.6692          |
| 8.2895        | 9.0   | 225  | 8.4222          |
| 8.067         | 10.0  | 250  | 8.2689          |
| 7.7922        | 11.0  | 275  | 8.1862          |
| 7.702         | 12.0  | 300  | 8.0916          |
| 7.5801        | 13.0  | 325  | 7.9765          |
| 7.4381        | 14.0  | 350  | 7.7605          |
| 7.4223        | 15.0  | 375  | 7.4846          |
| 7.0379        | 16.0  | 400  | 7.3010          |
| 6.9279        | 17.0  | 425  | 7.1606          |
| 6.7912        | 18.0  | 450  | 7.0390          |
| 6.7047        | 19.0  | 475  | 6.9686          |
| 6.5986        | 20.0  | 500  | 6.9092          |
| 6.5577        | 21.0  | 525  | 6.8427          |
| 6.4589        | 22.0  | 550  | 6.7866          |
| 6.3207        | 23.0  | 575  | 6.7021          |
| 1.1695        | 24.0  | 600  | 0.7696          |
| 0.7697        | 25.0  | 625  | 0.6522          |
| 0.6978        | 26.0  | 650  | 0.6488          |
| 0.6832        | 27.0  | 675  | 0.6470          |
| 0.7033        | 28.0  | 700  | 0.6322          |
| 0.692         | 29.0  | 725  | 0.6369          |
| 0.6703        | 30.0  | 750  | 0.6372          |
| 0.6781        | 31.0  | 775  | 0.6364          |
| 0.677         | 32.0  | 800  | 0.6252          |
| 0.6632        | 33.0  | 825  | 0.6301          |
| 0.6684        | 34.0  | 850  | 0.6254          |
| 0.6823        | 35.0  | 875  | 0.6312          |
| 0.6665        | 36.0  | 900  | 0.6328          |
| 0.6583        | 37.0  | 925  | 0.6256          |


### Framework versions

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