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-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-intra_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: 0.6279

## 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 |
|:-------------:|:-----:|:----:|:---------------:|
| 19.7945       | 1.0   | 25   | 24.1161         |
| 18.755        | 2.0   | 50   | 19.9773         |
| 18.2706       | 3.0   | 75   | 11.6905         |
| 16.8867       | 4.0   | 100  | 10.8195         |
| 15.645        | 5.0   | 125  | 10.3424         |
| 12.6568       | 6.0   | 150  | 9.3585          |
| 10.9942       | 7.0   | 175  | 9.1290          |
| 9.2494        | 8.0   | 200  | 8.8652          |
| 8.4954        | 9.0   | 225  | 8.5857          |
| 8.1042        | 10.0  | 250  | 8.4259          |
| 7.8977        | 11.0  | 275  | 8.3043          |
| 7.8384        | 12.0  | 300  | 8.1858          |
| 7.7411        | 13.0  | 325  | 7.9134          |
| 7.3565        | 14.0  | 350  | 7.6255          |
| 7.2074        | 15.0  | 375  | 7.3867          |
| 7.0111        | 16.0  | 400  | 7.2259          |
| 6.9705        | 17.0  | 425  | 7.1460          |
| 6.8314        | 18.0  | 450  | 7.0866          |
| 6.7505        | 19.0  | 475  | 7.0398          |
| 6.6081        | 20.0  | 500  | 6.9983          |
| 6.7054        | 21.0  | 525  | 6.9523          |
| 6.5904        | 22.0  | 550  | 6.9090          |
| 6.4272        | 23.0  | 575  | 6.5798          |
| 0.9712        | 24.0  | 600  | 0.7144          |
| 0.7214        | 25.0  | 625  | 0.6178          |
| 0.6687        | 26.0  | 650  | 0.6174          |
| 0.6565        | 27.0  | 675  | 0.6148          |
| 0.6602        | 28.0  | 700  | 0.6140          |
| 0.6449        | 29.0  | 725  | 0.6121          |
| 0.648         | 30.0  | 750  | 0.6133          |
| 0.6425        | 31.0  | 775  | 0.6154          |
| 0.6505        | 32.0  | 800  | 0.6115          |
| 0.661         | 33.0  | 825  | 0.6128          |
| 0.6482        | 34.0  | 850  | 0.6108          |
| 0.6501        | 35.0  | 875  | 0.6137          |
| 0.6436        | 36.0  | 900  | 0.6086          |
| 0.6377        | 37.0  | 925  | 0.6107          |
| 0.6275        | 38.0  | 950  | 0.6116          |
| 0.6254        | 39.0  | 975  | 0.6113          |
| 0.6357        | 40.0  | 1000 | 0.6091          |
| 0.6443        | 41.0  | 1025 | 0.6095          |


### Framework versions

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