metadata
library_name: transformers
license: mit
base_model: EleutherAI/gpt-neo-125M
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: MD5_gpt_neo_v1.1.4
results: []
MD5_gpt_neo_v1.1.4
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: 8.4439
- Rouge1: 0.0706
- Rouge2: 0.0027
- Rougel: 0.0591
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 | 0.9956 | 112 | 1.2557 | 0.4506 | 0.3864 | 0.4424 |
| No log | 2.0 | 225 | 2.6798 | 0.2436 | 0.0318 | 0.1904 |
| No log | 2.9956 | 337 | 5.4290 | 0.1316 | 0.0166 | 0.1014 |
| No log | 4.0 | 450 | 8.2713 | 0.0840 | 0.0032 | 0.0668 |
| 7.8064 | 4.9778 | 560 | 8.4439 | 0.0706 | 0.0027 | 0.0591 |
Framework versions
- Transformers 4.46.1
- Pytorch 2.5.0+cu121
- Datasets 3.1.0
- Tokenizers 0.20.1