metadata
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: feedback-classification
results: []
feedback-classification
This model is a fine-tuned version of qarib/bert-base-qarib_far_9920k on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.0442
- Macro F1: 0.8311
- Accuracy: 0.8275
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: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Macro F1 | Accuracy |
|---|---|---|---|---|---|
| No log | 1.0 | 342 | 0.5528 | 0.7897 | 0.7851 |
| 0.5472 | 2.0 | 684 | 0.6922 | 0.8200 | 0.8129 |
| 0.2753 | 3.0 | 1026 | 0.9658 | 0.8113 | 0.8070 |
| 0.2753 | 4.0 | 1368 | 0.9768 | 0.8349 | 0.8304 |
| 0.1171 | 5.0 | 1710 | 1.0442 | 0.8311 | 0.8275 |
Framework versions
- Transformers 4.30.1
- Pytorch 2.0.1+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3