metadata
library_name: transformers
license: mit
base_model: EleutherAI/gpt-neo-125M
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: MD5_gpt_neo_v1.1.1
results: []
MD5_gpt_neo_v1.1.1
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: 0.5658
- Rouge1: 0.4856
- Rouge2: 0.3287
- Rougel: 0.4662
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 | 0.9935 | 77 | 0.4256 | 0.4794 | 0.3497 | 0.4794 |
No log | 2.0 | 155 | 0.4503 | 0.4916 | 0.3557 | 0.4727 |
No log | 2.9935 | 232 | 0.5194 | 0.4864 | 0.3525 | 0.4780 |
No log | 4.0 | 310 | 0.5605 | 0.4845 | 0.3240 | 0.4620 |
No log | 4.9677 | 385 | 0.5658 | 0.4856 | 0.3287 | 0.4662 |
Framework versions
- Transformers 4.46.1
- Pytorch 2.5.0+cu121
- Datasets 3.1.0
- Tokenizers 0.20.1