初始化项目,由ModelHub XC社区提供模型
Model: jadechoi/wizl_base_7b-fsv Source: Original Platform
This commit is contained in:
138
README.md
Normal file
138
README.md
Normal file
@@ -0,0 +1,138 @@
|
||||
---
|
||||
library_name: transformers
|
||||
license: apache-2.0
|
||||
base_model: Qwen/Qwen2.5-Coder-7B-Instruct
|
||||
tags:
|
||||
- axolotl
|
||||
- generated_from_trainer
|
||||
datasets:
|
||||
- train.jsonl
|
||||
model-index:
|
||||
- name: wizl_base_7b-fsv
|
||||
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: `0.12.2`
|
||||
```yaml
|
||||
base_model: Qwen/Qwen2.5-Coder-7B-Instruct
|
||||
|
||||
load_in_8bit: false
|
||||
load_in_4bit: false
|
||||
|
||||
datasets:
|
||||
- path: train.jsonl
|
||||
type: chat_template
|
||||
|
||||
dataset_prepared_path: last_run_prepared
|
||||
val_set_size: 0.01
|
||||
output_dir: ./outputs/out
|
||||
|
||||
adapter:
|
||||
lora_model_dir:
|
||||
|
||||
sequence_len: 5120
|
||||
sample_packing: false
|
||||
eval_sample_packing: false
|
||||
pad_to_sequence_len: false
|
||||
|
||||
plugins:
|
||||
- axolotl.integrations.liger.LigerPlugin
|
||||
liger_rope: true
|
||||
liger_rms_norm: true
|
||||
liger_swiglu: true
|
||||
liger_fused_linear_cross_entropy: true
|
||||
|
||||
wandb_project: wizl-base-m
|
||||
wandb_entity:
|
||||
wandb_watch:
|
||||
wandb_name: 8b-base-fsv
|
||||
wandb_log_model:
|
||||
|
||||
hub_model_id: jadechoi/wizl_base_7b-fsv
|
||||
|
||||
gradient_accumulation_steps: 4
|
||||
micro_batch_size: 16
|
||||
num_epochs: 3
|
||||
optimizer: adamw_torch_fused
|
||||
lr_scheduler: cosine
|
||||
learning_rate: 2e-5
|
||||
|
||||
bf16: true
|
||||
fp16:
|
||||
tf32: false
|
||||
|
||||
gradient_checkpointing:
|
||||
logging_steps: 1
|
||||
flash_attention: true
|
||||
eager_attention:
|
||||
|
||||
warmup_ratio: 0.05
|
||||
evals_per_epoch: 0
|
||||
saves_per_epoch: 1
|
||||
weight_decay: 0.01
|
||||
|
||||
fsdp:
|
||||
- full_shard
|
||||
- auto_wrap
|
||||
|
||||
fsdp_config:
|
||||
fsdp_state_dict_type: FULL_STATE_DICT
|
||||
fsdp_transformer_layer_cls_to_wrap: Qwen2DecoderLayer
|
||||
fsdp_activation_checkpointing: true
|
||||
|
||||
# save_first_step: true # uncomment this to validate checkpoint saving works with your config
|
||||
```
|
||||
|
||||
</details><br>
|
||||
|
||||
# wizl_base_7b-fsv
|
||||
|
||||
This model is a fine-tuned version of [Qwen/Qwen2.5-Coder-7B-Instruct](https://huggingface.co/Qwen/Qwen2.5-Coder-7B-Instruct) on the train.jsonl dataset.
|
||||
|
||||
## 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: 2e-05
|
||||
- train_batch_size: 16
|
||||
- eval_batch_size: 16
|
||||
- seed: 42
|
||||
- distributed_type: multi-GPU
|
||||
- num_devices: 2
|
||||
- gradient_accumulation_steps: 4
|
||||
- total_train_batch_size: 128
|
||||
- total_eval_batch_size: 32
|
||||
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED 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: 11
|
||||
- training_steps: 220
|
||||
|
||||
### Training results
|
||||
|
||||
|
||||
|
||||
### Framework versions
|
||||
|
||||
- Transformers 4.55.2
|
||||
- Pytorch 2.6.0+cu124
|
||||
- Datasets 4.0.0
|
||||
- Tokenizers 0.21.4
|
||||
Reference in New Issue
Block a user