---
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-frequency-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-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: 1.2148

## 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 |
|:-------------:|:-----:|:----:|:---------------:|
| 19.9179       | 1.0   | 44   | 23.0110         |
| 15.7039       | 2.0   | 88   | 11.5544         |
| 10.0821       | 3.0   | 132  | 9.0299          |
| 8.6626        | 4.0   | 176  | 8.7380          |
| 8.0831        | 5.0   | 220  | 8.5723          |
| 8.0781        | 6.0   | 264  | 8.4705          |
| 7.9258        | 7.0   | 308  | 8.3030          |
| 7.7266        | 8.0   | 352  | 7.8865          |
| 7.2525        | 9.0   | 396  | 7.4655          |
| 7.0455        | 10.0  | 440  | 7.2241          |
| 6.852         | 11.0  | 484  | 7.0989          |
| 6.7656        | 12.0  | 528  | 6.9915          |
| 0.9781        | 13.0  | 572  | 0.7604          |
| 0.8277        | 14.0  | 616  | 0.7302          |
| 0.8107        | 15.0  | 660  | 0.7269          |
| 0.7979        | 16.0  | 704  | 0.7203          |
| 0.787         | 17.0  | 748  | 0.7190          |
| 0.784         | 18.0  | 792  | 0.7176          |
| 0.7723        | 19.0  | 836  | 0.7162          |
| 0.7689        | 20.0  | 880  | 0.7157          |
| 0.7627        | 21.0  | 924  | 0.7137          |
| 0.7691        | 22.0  | 968  | 0.7156          |
| 0.7728        | 23.0  | 1012 | 0.7139          |
| 0.7586        | 24.0  | 1056 | 0.7136          |
| 0.7508        | 25.0  | 1100 | 0.7130          |
| 0.7754        | 26.0  | 1144 | 0.7096          |
| 0.7449        | 27.0  | 1188 | 0.7117          |
| 0.769         | 28.0  | 1232 | 0.7073          |
| 0.7562        | 29.0  | 1276 | 0.7081          |
| 0.7597        | 30.0  | 1320 | 0.7111          |
| 0.7649        | 31.0  | 1364 | 0.7072          |
| 0.7449        | 32.0  | 1408 | 0.7113          |
| 0.7431        | 33.0  | 1452 | 0.7103          |
| 0.7448        | 34.0  | 1496 | 0.7066          |
| 0.7409        | 35.0  | 1540 | 0.7056          |
| 0.7438        | 36.0  | 1584 | 0.7072          |
| 0.7545        | 37.0  | 1628 | 0.7041          |
| 0.7519        | 38.0  | 1672 | 0.7060          |
| 0.7546        | 39.0  | 1716 | 0.7042          |
| 0.7585        | 40.0  | 1760 | 0.7031          |
| 0.7491        | 41.0  | 1804 | 0.7074          |
| 0.7421        | 42.0  | 1848 | 0.7058          |
| 0.7471        | 43.0  | 1892 | 0.7108          |
| 0.758         | 44.0  | 1936 | 0.7041          |
| 0.7291        | 45.0  | 1980 | 0.7049          |


### Framework versions

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