File size: 2,013 Bytes
13ed3a4 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 |
---
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: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# tiny-3e-4lr+1152tbs+1ep+0.1wd
This model is a fine-tuned version of [meta-llama/Llama-2-13b-hf](https://huggingface.co/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
|