metadata
base_model: meta-llama/Llama-2-7b-hf
library_name: peft
license: llama2
metrics:
- rouge
tags:
- trl
- sft
- generated_from_trainer
model-index:
- name: meta-llama/Llama-2-7b-hf
results: []
meta-llama/Llama-2-7b-hf
This model is a fine-tuned version of meta-llama/Llama-2-7b-hf on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.2159
- Rouge1: 0.8791
- Rouge2: 0.7599
- Rougel: 0.8661
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: 0.0002
- train_batch_size: 2
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 4
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant
- lr_scheduler_warmup_ratio: 0.03
- num_epochs: 5
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel |
|---|---|---|---|---|---|---|
| 0.2548 | 0.9990 | 513 | 0.2430 | 0.8707 | 0.7454 | 0.8577 |
| 0.2351 | 2.0 | 1027 | 0.2333 | 0.8717 | 0.7503 | 0.8613 |
| 0.2108 | 2.9990 | 1540 | 0.2205 | 0.8745 | 0.7543 | 0.8634 |
| 0.1954 | 4.0 | 2054 | 0.2159 | 0.8791 | 0.7599 | 0.8661 |
| 0.1998 | 4.9951 | 2565 | 0.2147 | 0.8822 | 0.7606 | 0.8661 |
Framework versions
- PEFT 0.13.1
- Transformers 4.45.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.20.0