|
--- |
|
license: apache-2.0 |
|
tags: |
|
- generated_from_trainer |
|
metrics: |
|
- accuracy |
|
- precision |
|
- recall |
|
- f1 |
|
model-index: |
|
- name: distilroberta-base-finetuned-3d-sentiment |
|
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. --> |
|
|
|
# distilroberta-base-finetuned-3d-sentiment |
|
|
|
This model is a fine-tuned version of [distilroberta-base](https://huggingface.co/distilroberta-base) on the None dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.7236 |
|
- Accuracy: 0.7476 |
|
- Precision: 0.7515 |
|
- Recall: 0.7476 |
|
- F1: 0.7474 |
|
|
|
## 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: 2e-05 |
|
- train_batch_size: 16 |
|
- eval_batch_size: 16 |
|
- seed: 42 |
|
- gradient_accumulation_steps: 4 |
|
- total_train_batch_size: 64 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: linear |
|
- lr_scheduler_warmup_steps: 6381 |
|
- num_epochs: 7 |
|
- mixed_precision_training: Native AMP |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | |
|
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:---------:|:------:|:------:| |
|
| 0.7918 | 1.0 | 1595 | 0.7835 | 0.6718 | 0.6877 | 0.6718 | 0.6697 | |
|
| 0.6103 | 2.0 | 3190 | 0.7777 | 0.6923 | 0.7151 | 0.6923 | 0.6917 | |
|
| 0.5534 | 3.0 | 4785 | 0.6858 | 0.7132 | 0.7250 | 0.7132 | 0.7108 | |
|
| 0.4998 | 4.0 | 6380 | 0.6715 | 0.7333 | 0.7398 | 0.7333 | 0.7325 | |
|
| 0.4327 | 5.0 | 7975 | 0.6745 | 0.7421 | 0.7463 | 0.7421 | 0.7420 | |
|
| 0.3534 | 6.0 | 9570 | 0.7236 | 0.7476 | 0.7515 | 0.7476 | 0.7474 | |
|
| 0.2926 | 7.0 | 11165 | 0.7916 | 0.7456 | 0.7510 | 0.7456 | 0.7457 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.26.1 |
|
- Pytorch 1.13.1+cu117 |
|
- Datasets 2.10.1 |
|
- Tokenizers 0.13.3 |
|
|
