metadata
library_name: transformers
license: mit
base_model: EleutherAI/gpt-neo-125M
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: MD5_gpt_neo_v1.3
results: []
MD5_gpt_neo_v1.3
This model is a fine-tuned version of EleutherAI/gpt-neo-125M on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 6.1987
- Rouge1: 0.0630
- Rouge2: 0.0081
- Rougel: 0.0461
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: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 4
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel |
|---|---|---|---|---|---|---|
| No log | 0.9961 | 129 | 4.0786 | 0.0876 | 0.0187 | 0.0674 |
| No log | 2.0 | 259 | 4.9529 | 0.0659 | 0.0125 | 0.0519 |
| No log | 2.9961 | 388 | 5.6868 | 0.0599 | 0.0090 | 0.0470 |
| 8.7097 | 4.0 | 518 | 6.0029 | 0.0611 | 0.0075 | 0.0446 |
| 8.7097 | 4.9807 | 645 | 6.1987 | 0.0630 | 0.0081 | 0.0461 |
Framework versions
- Transformers 4.46.1
- Pytorch 2.5.0+cu121
- Datasets 3.1.0
- Tokenizers 0.20.1