metadata
license: mit
base_model: roberta-base
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: intent-classifyV2
results: []
intent-classifyV2
This model is a fine-tuned version of roberta-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0041
- Accuracy: 0.9961
- Precision: 0.9961
- Recall: 0.9961
- F1: 0.9961
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: 1e-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: 4
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 64 | 0.0093 | 1.0 | 1.0 | 1.0 | 1.0 |
| No log | 2.0 | 128 | 0.0057 | 0.9961 | 0.9961 | 0.9961 | 0.9961 |
| No log | 3.0 | 192 | 0.0066 | 0.9961 | 0.9961 | 0.9961 | 0.9961 |
| No log | 4.0 | 256 | 0.0041 | 0.9961 | 0.9961 | 0.9961 | 0.9961 |
Framework versions
- Transformers 4.38.1
- Pytorch 2.2.1+cu121
- Datasets 2.15.0
- Tokenizers 0.15.2