metadata
license: apache-2.0
base_model: mHossain/ml_sum_v2
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: ml_sum_v3
results: []
ml_sum_v3
This model is a fine-tuned version of mHossain/ml_sum_v2 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: nan
- Rouge1: 0.0
- Rouge2: 0.0
- Rougel: 0.0
- Rougelsum: 0.0
- Gen Len: 0.0
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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 5000
- num_epochs: 4
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|---|---|---|---|---|---|---|---|---|
| No log | 1.0 | 312 | 0.3728 | 0.0844 | 0.0536 | 0.0844 | 0.0844 | 19.0 |
| 0.4276 | 2.0 | 625 | 0.3728 | 0.0844 | 0.0536 | 0.0844 | 0.0844 | 19.0 |
| 0.4276 | 3.0 | 937 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| 0.7627 | 3.99 | 1248 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
Framework versions
- Transformers 4.38.2
- Pytorch 2.1.0+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2