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---
library_name: transformers
license: mit
base_model: ByteDance-Seed/Seed-Coder-8B-Instruct
tags:
- generated_from_trainer
datasets:
- data_clean.jsonl
model-index:
- name: out-seedcoder-new
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: `0.13.0.dev0`
```yaml
base_model: ByteDance-Seed/Seed-Coder-8B-Instruct
bf16: true
dataset_prepared_path: last_run_prepared
# Dataset configuration for instruction/input/output format
datasets:
- chat_template: tokenizer_default
field_messages: messages
message_field_content: content
message_field_role: role
path: data_clean.jsonl
roles:
assistant:
- assistant
system:
- system
user:
- user
type: chat_template
debug: null
deepspeed: /osmosis/zero2.json
early_stopping_patience: null
flash_attention: true
fp16: null
fsdp: null
fsdp_config: null
gradient_accumulation_steps: 1
gradient_checkpointing: true
gradient_checkpointing_kwargs:
use_reentrant: false
group_by_length: false
learning_rate: 0.00001
liger_fused_linear_cross_entropy: true
liger_glu_activation: true
liger_layer_norm: true
liger_rms_norm: true
liger_rope: true
logging_steps: 1
lr_scheduler: cosine
max_grad_norm: 1
micro_batch_size: 16
model_type: AutoModelForCausalLM
num_epochs: 1
optimizer: adamw_torch
output_dir: ./out-seedcoder-new
pad_to_sequence_len: true
plugins:
- axolotl.integrations.liger.LigerPlugin
resume_from_checkpoint: null
sample_packing: false
save_steps: 60
save_total_limit: 100
sequence_len: 4096
# special_tokens:
# eos_token: <|im_end|>
strict: false
tf32: false
tokenizer_type: AutoTokenizer
train_on_inputs: false
trust_remote_code: true
val_set_size: 0.0
wandb_project: seedcoder
wandb_log_model: null
wandb_name: No-mods-bytedance-seedcoder-8b-instruct-full-64-very-new
wandb_watch: null
warmup_ratio: 0.05
weight_decay: 0.0
xformers_attention: null
```
</details><br>
# out-seedcoder-new
This model is a fine-tuned version of [ByteDance-Seed/Seed-Coder-8B-Instruct](https://huggingface.co/ByteDance-Seed/Seed-Coder-8B-Instruct) on the data_clean.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: 1e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- total_train_batch_size: 64
- total_eval_batch_size: 64
- optimizer: Use OptimizerNames.ADAMW_TORCH 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: 22
- training_steps: 441
### Training results
### Framework versions
- Transformers 4.57.1
- Pytorch 2.8.0+cu128
- Datasets 4.3.0
- Tokenizers 0.22.1
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