metadata
library_name: transformers
license: mit
base_model: EleutherAI/gpt-neo-1.3B
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: gpt-medmentions
results: []
gpt-medmentions
This model is a fine-tuned version of EleutherAI/gpt-neo-1.3B on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.4512
- Precision: 0.4110
- Recall: 0.5052
- F1: 0.4533
- Accuracy: 0.4334
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: 5e-05
- train_batch_size: 4
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 2
- total_train_batch_size: 8
- total_eval_batch_size: 16
- 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: 5.0
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| 1.2514 | 1.0 | 2917 | 1.2192 | 0.4016 | 0.3853 | 0.3933 | 0.4191 |
| 1.0825 | 2.0 | 5834 | 1.1892 | 0.4234 | 0.6373 | 0.5088 | 0.4324 |
| 0.9093 | 3.0 | 8751 | 1.2419 | 0.4105 | 0.4848 | 0.4446 | 0.4308 |
| 0.7938 | 4.0 | 11668 | 1.3655 | 0.3774 | 0.3369 | 0.3560 | 0.4301 |
| 0.746 | 5.0 | 14585 | 1.4512 | 0.4110 | 0.5052 | 0.4533 | 0.4334 |
Framework versions
- Transformers 4.50.3
- Pytorch 2.6.0+cu124
- Datasets 3.5.0
- Tokenizers 0.21.1