---
license: apache-2.0
base_model: google/t5-v1_1-large
tags:
- generated_from_trainer
model-index:
- name: Sentiment-google-t5-v1_1-large-inter_model-sorted-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. -->

# Sentiment-google-t5-v1_1-large-inter_model-sorted-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 |
|:-------------:|:-----:|:----:|:---------------:|
| 20.5922       | 1.0   | 44   | 24.6172         |
| 16.3048       | 2.0   | 88   | 12.1742         |
| 11.2971       | 3.0   | 132  | 10.1133         |
| 9.1562        | 4.0   | 176  | 8.7959          |
| 8.2587        | 5.0   | 220  | 8.5608          |
| 8.1239        | 6.0   | 264  | 8.4644          |
| 7.9281        | 7.0   | 308  | 8.3953          |
| 7.9676        | 8.0   | 352  | 8.2317          |
| 7.5012        | 9.0   | 396  | 7.7257          |
| 7.1769        | 10.0  | 440  | 7.3715          |
| 6.9303        | 11.0  | 484  | 7.1975          |
| 6.8629        | 12.0  | 528  | 7.0684          |
| 6.6057        | 13.0  | 572  | 6.9544          |
| 0.9049        | 14.0  | 616  | 0.6979          |
| 0.7327        | 15.0  | 660  | 0.6557          |
| 0.712         | 16.0  | 704  | 0.6521          |
| 0.7003        | 17.0  | 748  | 0.6520          |
| 0.7145        | 18.0  | 792  | 0.6503          |
| 0.6983        | 19.0  | 836  | 0.6504          |
| 0.6943        | 20.0  | 880  | 0.6481          |
| 0.6912        | 21.0  | 924  | 0.6479          |
| 0.6945        | 22.0  | 968  | 0.6467          |
| 0.6929        | 23.0  | 1012 | 0.6493          |
| 0.6902        | 24.0  | 1056 | 0.6479          |
| 0.6853        | 25.0  | 1100 | 0.6444          |
| 0.6881        | 26.0  | 1144 | 0.6438          |
| 0.6774        | 27.0  | 1188 | 0.6462          |
| 0.6921        | 28.0  | 1232 | 0.6456          |
| 0.6852        | 29.0  | 1276 | 0.6450          |
| 0.6763        | 30.0  | 1320 | 0.6448          |
| 0.6858        | 31.0  | 1364 | 0.6433          |
| 0.6789        | 32.0  | 1408 | 0.6450          |
| 0.6819        | 33.0  | 1452 | 0.6457          |
| 0.6804        | 34.0  | 1496 | 0.6458          |
| 0.6713        | 35.0  | 1540 | 0.6450          |
| 0.6781        | 36.0  | 1584 | 0.6437          |


### Framework versions

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