metadata
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: SA-roberta-e3-w1-5-b16-w0.01-data2
results: []
SA-roberta-e3-w1-5-b16-w0.01-data2
This model is a fine-tuned version of Amalq/autotrain-smm4h_large_roberta_clean-874027878 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.7680
- Accuracy: 0.9021
- F1: 0.8646
- Precision: 0.8921
- Recall: 0.8388
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
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
|---|---|---|---|---|---|---|---|
| 0.2612 | 1.0 | 581 | 0.4296 | 0.9021 | 0.8721 | 0.8499 | 0.8955 |
| 0.1252 | 2.0 | 1162 | 0.7605 | 0.8977 | 0.8571 | 0.8932 | 0.8239 |
| 0.0567 | 3.0 | 1743 | 0.7680 | 0.9021 | 0.8646 | 0.8921 | 0.8388 |
Framework versions
- Transformers 4.30.2
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3