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

# Sentiment-google-t5-v1_1-large-intra_model-frequency-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: 1.5938

## 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 |
|:-------------:|:-----:|:----:|:---------------:|
| 20.8407       | 1.0   | 44   | 24.0718         |
| 19.0527       | 2.0   | 88   | 19.4828         |
| 13.4842       | 3.0   | 132  | 11.5393         |
| 10.8626       | 4.0   | 176  | 10.8995         |
| 10.3562       | 5.0   | 220  | 10.7412         |
| 10.008        | 6.0   | 264  | 10.5271         |
| 9.8519        | 7.0   | 308  | 10.3934         |
| 9.6414        | 8.0   | 352  | 10.0350         |
| 8.9978        | 9.0   | 396  | 9.4410          |
| 8.6735        | 10.0  | 440  | 9.0569          |
| 8.3986        | 11.0  | 484  | 8.8689          |
| 8.2999        | 12.0  | 528  | 8.7266          |
| 1.7304        | 13.0  | 572  | 1.1034          |
| 1.165         | 14.0  | 616  | 1.0495          |
| 1.0776        | 15.0  | 660  | 1.0454          |
| 1.0862        | 16.0  | 704  | 1.0384          |
| 1.0628        | 17.0  | 748  | 1.0318          |
| 1.0547        | 18.0  | 792  | 1.0329          |
| 1.0513        | 19.0  | 836  | 1.0381          |
| 1.0389        | 20.0  | 880  | 1.0247          |
| 1.0381        | 21.0  | 924  | 1.0231          |
| 1.056         | 22.0  | 968  | 1.0160          |
| 1.0508        | 23.0  | 1012 | 1.0171          |
| 1.0514        | 24.0  | 1056 | 1.0143          |
| 1.0373        | 25.0  | 1100 | 1.0128          |
| 1.0295        | 26.0  | 1144 | 1.0129          |
| 1.0178        | 27.0  | 1188 | 1.0110          |
| 1.0216        | 28.0  | 1232 | 1.0056          |
| 1.0355        | 29.0  | 1276 | 1.0084          |
| 1.0276        | 30.0  | 1320 | 1.0017          |
| 1.0066        | 31.0  | 1364 | 1.0080          |
| 1.0107        | 32.0  | 1408 | 1.0044          |
| 1.0165        | 33.0  | 1452 | 1.0019          |


### Framework versions

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