metadata
library_name: transformers
base_model: meta-llama/Meta-Llama-3-8B
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: context
results: []
context
This model is a fine-tuned version of meta-llama/Meta-Llama-3-8B on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 3.7005
- Accuracy: 0.4548
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: 40
- eval_batch_size: 40
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 160
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- num_epochs: 3.0
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.7716 | 0.6479 | 500 | 3.7005 | 0.4548 |
| 0.3675 | 1.2958 | 1000 | 3.8487 | 0.4565 |
| 0.2102 | 1.9436 | 1500 | 3.9705 | 0.4568 |
| 0.1164 | 2.5915 | 2000 | 4.1546 | 0.4570 |
Framework versions
- Transformers 4.45.0.dev0
- Pytorch 2.3.1+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1