|
--- |
|
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-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. --> |
|
|
|
# Sentiment-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: 5.1523 |
|
|
|
## 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 | |
|
|:-------------:|:-----:|:----:|:---------------:| |
|
| 21.4519 | 1.0 | 44 | 23.5551 | |
|
| 18.9968 | 2.0 | 88 | 14.8263 | |
|
| 14.9431 | 3.0 | 132 | 12.4969 | |
|
| 12.6115 | 4.0 | 176 | 11.0088 | |
|
| 10.6403 | 5.0 | 220 | 10.5915 | |
|
| 9.9328 | 6.0 | 264 | 10.3356 | |
|
| 9.7009 | 7.0 | 308 | 10.2266 | |
|
| 9.6314 | 8.0 | 352 | 10.0653 | |
|
| 9.0124 | 9.0 | 396 | 9.4660 | |
|
| 8.5964 | 10.0 | 440 | 8.9690 | |
|
| 8.2786 | 11.0 | 484 | 8.7360 | |
|
| 8.1874 | 12.0 | 528 | 8.5747 | |
|
| 7.731 | 13.0 | 572 | 8.2712 | |
|
| 1.0229 | 14.0 | 616 | 0.8619 | |
|
| 0.9062 | 15.0 | 660 | 0.8607 | |
|
| 0.9159 | 16.0 | 704 | 0.8539 | |
|
| 0.9008 | 17.0 | 748 | 0.8525 | |
|
| 0.8876 | 18.0 | 792 | 0.8460 | |
|
| 0.8877 | 19.0 | 836 | 0.8504 | |
|
| 0.8792 | 20.0 | 880 | 0.8484 | |
|
| 0.8778 | 21.0 | 924 | 0.8492 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.34.0 |
|
- Pytorch 2.1.0+cu121 |
|
- Datasets 2.6.1 |
|
- Tokenizers 0.14.1 |
|
|
