metadata
base_model: meta-llama/Llama-2-13b-hf
tags:
- generated_from_trainer
datasets:
- yhavinga/mc4_nl_cleaned
model-index:
- name: tiny-3e-4lr+1152tbs+1ep+0.1wd
results: []
tiny-3e-4lr+1152tbs+1ep+0.1wd
This model is a fine-tuned version of meta-llama/Llama-2-13b-hf on the yhavinga/mc4_nl_cleaned micro dataset. It achieves the following results on the evaluation set:
- Loss: 1.7676
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: 0.0003
- train_batch_size: 12
- eval_batch_size: 12
- seed: 42
- distributed_type: multi-GPU
- num_devices: 16
- gradient_accumulation_steps: 6
- total_train_batch_size: 1152
- total_eval_batch_size: 192
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.03
- num_epochs: 1
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 1.8784 | 0.09 | 90 | 1.8820 |
| 1.8344 | 0.19 | 180 | 1.8542 |
| 1.8351 | 0.28 | 270 | 1.8355 |
| 1.8206 | 0.37 | 360 | 1.8212 |
| 1.8021 | 0.47 | 450 | 1.8088 |
| 1.8102 | 0.56 | 540 | 1.7982 |
| 1.7991 | 0.65 | 630 | 1.7890 |
| 1.7788 | 0.74 | 720 | 1.7811 |
| 1.7915 | 0.84 | 810 | 1.7742 |
| 1.7715 | 0.93 | 900 | 1.7676 |
Framework versions
- Transformers 4.31.0.dev0
- Pytorch 2.0.1+cu117
- Datasets 2.13.1
- Tokenizers 0.13.3