metadata
tags:
- generated_from_trainer
model-index:
- name: b2b_cnn_retrain
results: []
b2b_cnn_retrain
This model is a fine-tuned version of on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 8.0538
- Rouge2 Precision: 0.0033
- Rouge2 Recall: 0.0089
- Rouge2 Fmeasure: 0.0048
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: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 32
- total_train_batch_size: 512
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 5
- training_steps: 50
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge2 Precision | Rouge2 Recall | Rouge2 Fmeasure |
|---|---|---|---|---|---|---|
| 0.587 | 5.0 | 5 | 8.3529 | 0.0 | 0.0 | 0.0 |
| 0.4646 | 10.0 | 10 | 8.1390 | 0.0033 | 0.003 | 0.0031 |
| 0.4335 | 15.0 | 15 | 8.1031 | 0.0 | 0.0 | 0.0 |
| 0.3966 | 20.0 | 20 | 8.1701 | 0.0 | 0.0 | 0.0 |
| 0.3476 | 25.0 | 25 | 8.2264 | 0.0 | 0.0 | 0.0 |
| 0.2928 | 30.0 | 30 | 8.0323 | 0.0029 | 0.017 | 0.0049 |
| 0.244 | 35.0 | 35 | 7.9815 | 0.0024 | 0.0057 | 0.0034 |
| 0.2059 | 40.0 | 40 | 7.9555 | 0.0035 | 0.0114 | 0.0053 |
| 0.1791 | 45.0 | 45 | 8.0112 | 0.0046 | 0.0114 | 0.0066 |
| 0.1637 | 50.0 | 50 | 8.0538 | 0.0033 | 0.0089 | 0.0048 |
Framework versions
- Transformers 4.41.1
- Pytorch 2.3.0+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1