metadata
library_name: transformers
license: mit
base_model: EleutherAI/gpt-neo-125M
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: MD5_gpt_neo_v1.1.3
results: []
MD5_gpt_neo_v1.1.3
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: 0.0538
- Rouge1: 0.5076
- Rouge2: 0.2548
- Rougel: 0.4743
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 | 1.0 | 70 | 0.0628 | 0.4870 | 0.2269 | 0.4475 |
| No log | 2.0 | 140 | 0.0566 | 0.4913 | 0.2367 | 0.4607 |
| No log | 3.0 | 210 | 0.0545 | 0.4972 | 0.2484 | 0.4667 |
| No log | 4.0 | 280 | 0.0544 | 0.5023 | 0.2586 | 0.4749 |
| No log | 5.0 | 350 | 0.0538 | 0.5076 | 0.2548 | 0.4743 |
Framework versions
- Transformers 4.46.1
- Pytorch 2.5.0+cu121
- Datasets 3.1.0
- Tokenizers 0.20.1