---
library_name: transformers
tags:
- generated_from_trainer
datasets:
- json
model-index:
- name: raid/hoangpv4/models/specialized_llm_8b_base_10000
results: []
---
[
](https://github.com/axolotl-ai-cloud/axolotl)
See axolotl config
axolotl version: `0.6.0`
```yaml
base_model: /raid/HUB_LLM/Llama-3.1-8B
model_type: LlamaForCausalLM
tokenizer_type: AutoTokenizer
load_in_8bit: false
load_in_4bit: false
strict: false
chat_template: llama3
datasets:
- path: json
data_files:
- /workspace/home/namb/hoangpv4/kg_fact_checking/data/train_specialized_llm/data_ready_to_train_10000.jsonl
type: chat_template
field_messages: messages
message_field_role: role
message_field_content: content
train_on_eos: turn
val_set_size: 0.0
output_dir: /raid/hoangpv4/models/specialized_llm_8b_base_10000
sequence_len: 256
sample_packing: false
pad_to_sequence_len: true
wandb_project:
wandb_entity:
wandb_watch:
wandb_name:
wandb_log_model:
gradient_accumulation_steps: 1
micro_batch_size: 8
num_epochs: 2
optimizer: paged_adamw_8bit
lr_scheduler: constant
learning_rate: 2e-5
train_on_inputs: false
group_by_length: false
bf16: auto
fp16:
tf32: false
gradient_checkpointing: true
gradient_checkpointing_kwargs:
use_reentrant: false
early_stopping_patience:
resume_from_checkpoint:
logging_steps: 5
xformers_attention:
flash_attention: true
warmup_steps: 100
evals_per_epoch: 2
eval_table_size:
saves_per_epoch: 1
debug:
deepspeed: /workspace/home/namb/hoangpv4/kg_fact_checking/axolotl_config/zero3.json
weight_decay: 0.0
fsdp:
fsdp_config:
special_tokens:
pad_token: <|end_of_text|>
eos_token: <|eot_id|>
tokens:
- ""
- ""
- "~"
```
# raid/hoangpv4/models/specialized_llm_8b_base_10000
This model was trained from scratch on the json 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: 8
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- total_train_batch_size: 32
- total_eval_batch_size: 32
- optimizer: Use OptimizerNames.PAGED_ADAMW_8BIT with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: constant
- lr_scheduler_warmup_steps: 100
- num_epochs: 2
### Training results
### Framework versions
- Transformers 4.47.1
- Pytorch 2.3.1+cu121
- Datasets 3.1.0
- Tokenizers 0.21.0