---
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-sorted-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-sorted-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: 0.6221

## 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 |
|:-------------:|:-----:|:----:|:---------------:|
| 20.7839       | 1.0   | 25   | 25.3269         |
| 20.0699       | 2.0   | 50   | 21.6598         |
| 19.1726       | 3.0   | 75   | 21.6652         |
| 17.222        | 4.0   | 100  | 15.0207         |
| 14.7785       | 5.0   | 125  | 10.0582         |
| 12.0504       | 6.0   | 150  | 9.4216          |
| 11.1003       | 7.0   | 175  | 9.0795          |
| 9.259         | 8.0   | 200  | 8.7145          |
| 8.4364        | 9.0   | 225  | 8.5969          |
| 8.0676        | 10.0  | 250  | 8.5227          |
| 7.975         | 11.0  | 275  | 8.4316          |
| 7.9747        | 12.0  | 300  | 8.3585          |
| 7.8189        | 13.0  | 325  | 8.2247          |
| 7.6989        | 14.0  | 350  | 7.9381          |
| 7.3673        | 15.0  | 375  | 7.5837          |
| 7.234         | 16.0  | 400  | 7.3654          |
| 7.0686        | 17.0  | 425  | 7.2360          |
| 6.8718        | 18.0  | 450  | 7.1579          |
| 6.8965        | 19.0  | 475  | 7.1054          |
| 6.7995        | 20.0  | 500  | 7.0521          |
| 6.6533        | 21.0  | 525  | 6.9925          |
| 6.5043        | 22.0  | 550  | 6.8905          |
| 1.2868        | 23.0  | 575  | 0.6607          |
| 0.6465        | 24.0  | 600  | 0.5685          |
| 0.6195        | 25.0  | 625  | 0.5598          |
| 0.5945        | 26.0  | 650  | 0.5600          |
| 0.594         | 27.0  | 675  | 0.5565          |
| 0.5851        | 28.0  | 700  | 0.5554          |
| 0.5986        | 29.0  | 725  | 0.5510          |
| 0.5854        | 30.0  | 750  | 0.5502          |
| 0.6018        | 31.0  | 775  | 0.5525          |
| 0.5922        | 32.0  | 800  | 0.5482          |
| 0.5871        | 33.0  | 825  | 0.5504          |
| 0.586         | 34.0  | 850  | 0.5498          |
| 0.5847        | 35.0  | 875  | 0.5498          |
| 0.5954        | 36.0  | 900  | 0.5502          |
| 0.5892        | 37.0  | 925  | 0.5470          |
| 0.5853        | 38.0  | 950  | 0.5510          |
| 0.5892        | 39.0  | 975  | 0.5483          |
| 0.5879        | 40.0  | 1000 | 0.5491          |
| 0.5768        | 41.0  | 1025 | 0.5488          |
| 0.5886        | 42.0  | 1050 | 0.5530          |


### Framework versions

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