---
base_model: SeaLLMs/SeaLLM3-7B-Chat
library_name: peft
license: other
tags:
- axolotl
- generated_from_trainer
model-index:
- name: proof-reading-SeaLLM3-7B-Chat-3090-v5
  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: SeaLLMs/SeaLLM3-7B-Chat
trust_remote_code: true

load_in_8bit: false
load_in_4bit: true
strict: false

datasets:
  - path: Tippawan/pr-5-seallm-messages-only
    type: sharegpt
    conversation: chatml
    field_messages: messages
chat_template: chatml
dataset_prepared_path:
val_set_size: 0.00 #editted 2
output_dir: ./outputs/outputs_name

sequence_len: 2048
sample_packing: false
eval_sample_packing: false
pad_to_sequence_len: false

push_to_hub: true
hub_model_id: Tippawan/proof-reading-SeaLLM3-7B-Chat-3090-v5  # Replace with your Hugging Face repo ID
use_auth_token: true  # Ensure you have set your Hugging Face API token in the environment
hub_private_repo: true  # Set to true if you want the repository to be private
hub_strategy: all_checkpoints
save_total_limit: 3
load_best_model_at_end: true

adapter: lora
lora_model_dir: Tippawan/proof-reading-SeaLLM3-7B-Chat-3090-v4
lora_r: 16
lora_alpha: 32
lora_dropout: 0.05
lora_target_linear: true
lora_fan_in_fan_out:

wandb_project: proof-reading-SeaLLM3-7B-Chat-3090-v5
wandb_entity: 
wandb_watch:
wandb_name:
wandb_log_model:

gradient_accumulation_steps: 4
micro_batch_size: 8
num_epochs: 10 #editted 3
optimizer: adamw_torch
lr_scheduler: cosine
learning_rate: 0.0002

train_on_inputs: false
group_by_length: false
bf16: auto
fp16: 
tf32: true

gradient_checkpointing: true
early_stopping_patience:
resume_from_checkpoint:
local_rank:
logging_steps: 1
xformers_attention:
flash_attention: true
seed: 42
warmup_steps: 10
evals_per_epoch: 1
saves_per_epoch: 1
debug:
deepspeed:
weight_decay: 0.0
fsdp:
fsdp_config:
special_tokens:
```

</details><br>

# proof-reading-SeaLLM3-7B-Chat-3090-v5

This model is a fine-tuned version of [SeaLLMs/SeaLLM3-7B-Chat](https://huggingface.co/SeaLLMs/SeaLLM3-7B-Chat) on the None 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: 0.0002
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 10
- num_epochs: 10

### Training results



### Framework versions

- PEFT 0.12.0
- Transformers 4.45.0.dev0
- Pytorch 2.3.1+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1