---
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-dataset-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-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: 0.7983

## 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 |
|:-------------:|:-----:|:----:|:---------------:|
| 20.1785       | 1.0   | 44   | 24.2987         |
| 16.7918       | 2.0   | 88   | 13.0112         |
| 10.2722       | 3.0   | 132  | 9.1399          |
| 8.7351        | 4.0   | 176  | 8.7771          |
| 8.1648        | 5.0   | 220  | 8.6202          |
| 8.1662        | 6.0   | 264  | 8.5136          |
| 8.0042        | 7.0   | 308  | 8.3971          |
| 7.8946        | 8.0   | 352  | 8.1025          |
| 7.4059        | 9.0   | 396  | 7.6197          |
| 7.1363        | 10.0  | 440  | 7.3350          |
| 6.9292        | 11.0  | 484  | 7.1825          |
| 6.8455        | 12.0  | 528  | 7.0740          |
| 6.5296        | 13.0  | 572  | 6.9423          |
| 0.9019        | 14.0  | 616  | 0.6900          |
| 0.7584        | 15.0  | 660  | 0.6856          |
| 0.7245        | 16.0  | 704  | 0.6713          |
| 0.7189        | 17.0  | 748  | 0.6693          |
| 0.7258        | 18.0  | 792  | 0.6675          |
| 0.7222        | 19.0  | 836  | 0.6668          |
| 0.7112        | 20.0  | 880  | 0.6680          |
| 0.7125        | 21.0  | 924  | 0.6645          |
| 0.7038        | 22.0  | 968  | 0.6664          |
| 0.719         | 23.0  | 1012 | 0.6638          |
| 0.7022        | 24.0  | 1056 | 0.6621          |
| 0.6961        | 25.0  | 1100 | 0.6653          |
| 0.709         | 26.0  | 1144 | 0.6653          |
| 0.6969        | 27.0  | 1188 | 0.6633          |
| 0.7109        | 28.0  | 1232 | 0.6604          |
| 0.6965        | 29.0  | 1276 | 0.6617          |
| 0.7015        | 30.0  | 1320 | 0.6617          |
| 0.7098        | 31.0  | 1364 | 0.6609          |
| 0.6951        | 32.0  | 1408 | 0.6613          |
| 0.6881        | 33.0  | 1452 | 0.6631          |


### Framework versions

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