|
--- |
|
library_name: transformers |
|
license: apache-2.0 |
|
base_model: Qwen/Qwen2-0.5B |
|
tags: |
|
- axolotl |
|
- generated_from_trainer |
|
model-index: |
|
- name: 459779f2-cbce-4ec0-b11c-1dcdf92498d8 |
|
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. --> |
|
|
|
[<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) |
|
<details><summary>See axolotl config</summary> |
|
|
|
axolotl version: `0.4.1` |
|
```yaml |
|
base_model: Qwen/Qwen2-0.5B |
|
batch_size: 32 |
|
bf16: true |
|
chat_template: tokenizer_default_fallback_alpaca |
|
datasets: |
|
- data_files: |
|
- 745d2d05aaed18f4_train_data.json |
|
ds_type: json |
|
format: custom |
|
path: /workspace/input_data/745d2d05aaed18f4_train_data.json |
|
type: |
|
field_input: pos |
|
field_instruction: task |
|
field_output: query |
|
format: '{instruction} {input}' |
|
no_input_format: '{instruction}' |
|
system_format: '{system}' |
|
system_prompt: '' |
|
eval_steps: 20 |
|
flash_attention: true |
|
gpu_memory_limit: 80GiB |
|
gradient_checkpointing: true |
|
group_by_length: true |
|
hub_model_id: willtensora/459779f2-cbce-4ec0-b11c-1dcdf92498d8 |
|
hub_strategy: checkpoint |
|
learning_rate: 0.0002 |
|
logging_steps: 10 |
|
lr_scheduler: cosine |
|
max_steps: 2500 |
|
micro_batch_size: 4 |
|
model_type: AutoModelForCausalLM |
|
optimizer: adamw_bnb_8bit |
|
output_dir: /workspace/axolotl/configs |
|
pad_to_sequence_len: true |
|
resize_token_embeddings_to_32x: false |
|
sample_packing: false |
|
save_steps: 40 |
|
save_total_limit: 1 |
|
sequence_len: 2048 |
|
tokenizer_type: Qwen2TokenizerFast |
|
train_on_inputs: false |
|
trust_remote_code: true |
|
val_set_size: 0.1 |
|
wandb_entity: '' |
|
wandb_mode: online |
|
wandb_name: Qwen/Qwen2-0.5B-/workspace/input_data/745d2d05aaed18f4_train_data.json |
|
wandb_project: Gradients-On-Demand |
|
wandb_run: your_name |
|
wandb_runid: default |
|
warmup_ratio: 0.05 |
|
xformers_attention: true |
|
|
|
``` |
|
|
|
</details><br> |
|
|
|
# 459779f2-cbce-4ec0-b11c-1dcdf92498d8 |
|
|
|
This model is a fine-tuned version of [Qwen/Qwen2-0.5B](https://huggingface.co./Qwen/Qwen2-0.5B) on the None dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 2.4560 |
|
|
|
## 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: 4 |
|
- eval_batch_size: 4 |
|
- seed: 42 |
|
- distributed_type: multi-GPU |
|
- num_devices: 8 |
|
- total_train_batch_size: 32 |
|
- total_eval_batch_size: 32 |
|
- optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
|
- lr_scheduler_type: cosine |
|
- lr_scheduler_warmup_steps: 14 |
|
- training_steps: 291 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | |
|
|:-------------:|:------:|:----:|:---------------:| |
|
| No log | 0.0004 | 1 | 3.9660 | |
|
| 2.8207 | 0.0086 | 20 | 3.1038 | |
|
| 3.1247 | 0.0172 | 40 | 3.0989 | |
|
| 2.9411 | 0.0258 | 60 | 2.8986 | |
|
| 2.9915 | 0.0344 | 80 | 2.8742 | |
|
| 2.8038 | 0.0430 | 100 | 2.8405 | |
|
| 2.8518 | 0.0516 | 120 | 2.7728 | |
|
| 2.7079 | 0.0602 | 140 | 2.6985 | |
|
| 2.6076 | 0.0688 | 160 | 2.6416 | |
|
| 2.6172 | 0.0774 | 180 | 2.5695 | |
|
| 2.552 | 0.0860 | 200 | 2.5151 | |
|
| 2.5036 | 0.0946 | 220 | 2.4783 | |
|
| 2.4887 | 0.1032 | 240 | 2.4610 | |
|
| 2.4008 | 0.1118 | 260 | 2.4569 | |
|
| 2.424 | 0.1204 | 280 | 2.4560 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.46.0 |
|
- Pytorch 2.5.0+cu124 |
|
- Datasets 3.0.1 |
|
- Tokenizers 0.20.1 |
|
|