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---
license: other
library_name: peft
tags:
- generated_from_trainer
base_model: deepseek-ai/deepseek-coder-7b-instruct-v1.5
model-index:
- name: lora-logo_fix_full_deepseek7b_ds33i_lr_0.0002_alpha_512_r_512
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/OpenAccess-AI-Collective/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/OpenAccess-AI-Collective/axolotl)
<details><summary>See axolotl config</summary>
axolotl version: `0.4.0`
```yaml
adapter: lora
base_model: deepseek-ai/deepseek-coder-7b-instruct-v1.5
bf16: auto
dataset_prepared_path: ./logo_ds_preprocess_list_gpt35
datasets:
- path: ../logo/fix_deepseek_synthetic_training_data_full.jsonl
type:
field_instruction: input
field_output: output
format: '### Instruction:
{input}
### Response:
'
no_input_format: '{instruction}'
debug: null
deepspeed: ./deepspeed_configs/zero2.json
early_stopping_patience: null
eval_sample_packing: true
evals_per_epoch: 4
flash_attention: true
fp16: null
fsdp: null
fsdp_config: null
gradient_accumulation_steps: 1
gradient_checkpointing: true
group_by_length: false
is_llama_derived_model: true
learning_rate: 0.0002
load_in_4bit: false
load_in_8bit: true
local_rank: null
logging_steps: 1
lora_alpha: 512
lora_dropout: 0.05
lora_fan_in_fan_out: null
lora_model_dir: null
lora_r: 512
lora_target_linear: true
lr_scheduler: cosine
micro_batch_size: 8
model_type: AutoModelForCausalLM
num_epochs: 3
optimizer: adamw_bnb_8bit
output_dir: ./lora-logo_fix_full_deepseek7b_ds33i_lr_0.0002_alpha_512_r_512
pad_to_sequence_len: true
resume_from_checkpoint: null
s2_attention: null
sample_packing: true
saves_per_epoch: 1
sequence_len: 1800
special_tokens:
bos_token: "<\uFF5Cbegin\u2581of\u2581sentence\uFF5C>"
eos_token: <|EOT|>
strict: true
tf32: false
tokenizer_type: AutoTokenizer
train_on_inputs: false
val_set_size: 0.05
wandb_entity: null
wandb_log_model: null
wandb_name: logo_fix_full_deepseek7b_ds33i_lr_0.0002_alpha_512_r_512
wandb_project: pbe-axo
wandb_watch: null
warmup_steps: 20
weight_decay: 0.0
xformers_attention: null
```
</details><br>
# lora-logo_fix_full_deepseek7b_ds33i_lr_0.0002_alpha_512_r_512
This model is a fine-tuned version of [deepseek-ai/deepseek-coder-7b-instruct-v1.5](https://huggingface.co/deepseek-ai/deepseek-coder-7b-instruct-v1.5) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4023
## 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
- distributed_type: multi-GPU
- num_devices: 8
- total_train_batch_size: 64
- total_eval_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 20
- num_epochs: 3
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 2.3105 | 0.0 | 1 | 2.3643 |
| 0.463 | 0.25 | 78 | 0.4702 |
| 0.4169 | 0.5 | 156 | 0.4442 |
| 0.4411 | 0.75 | 234 | 0.4278 |
| 0.4635 | 1.0 | 312 | 0.4184 |
| 0.3626 | 1.23 | 390 | 0.4134 |
| 0.3622 | 1.48 | 468 | 0.4074 |
| 0.3903 | 1.73 | 546 | 0.4003 |
| 0.3737 | 1.98 | 624 | 0.3954 |
| 0.3169 | 2.21 | 702 | 0.4044 |
| 0.338 | 2.46 | 780 | 0.4030 |
| 0.3237 | 2.71 | 858 | 0.4022 |
| 0.2976 | 2.96 | 936 | 0.4023 |
### Framework versions
- PEFT 0.10.0
- Transformers 4.40.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0 |