Hugging Face's logo

afrias5
/
meta-codellama-34b-python-Score8192V4

PEFT
Safetensors
llama
axolotl
Generated from Trainer
Model card Files Community
meta-codellama-34b-python-Score8192V4
File size: 3,419 Bytes 
bafaa1c
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
 
---
library_name: peft
license: llama2
base_model: meta-llama/CodeLlama-34b-Python-hf
tags:
- axolotl
- generated_from_trainer
datasets:
- afrias5/datasetScoreFinal
model-index:
- name: meta-codellama-34b-python-Score8192V4
  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: `0.5.3.dev41+g5e9fa33f`
```yaml
base_model: meta-llama/CodeLlama-34b-Python-hf
model_type: LlamaForCausalLM
tokenizer_type: CodeLlamaTokenizer


load_in_8bit: false
load_in_4bit: false
strict: false


datasets:
  - path: afrias5/datasetScoreFinal
    type: alpaca
    field: text


# dataset_prepared_path: ./FinUpTagsNoTestNoExNew
val_set_size: 0
output_dir: models/meta-codellama-34b-python-Score8192V4
lora_model_dir: models/meta-codellama-34b-python-Score8192V4/checkpoint-55
auto_resume_from_checkpoints: true
sequence_len: 8192
sample_packing: true
pad_to_sequence_len: true
eval_sample_packing: False
adapter: lora
lora_model_dir:
lora_r: 2
lora_alpha: 16
lora_dropout: 0.05
lora_target_linear: true
lora_fan_in_fan_out:
lora_modules_to_save:
  - embed_tokens
  - lm_head


wandb_project: 'Code34bNewFeed'
wandb_entity:
wandb_watch:
wandb_run_id:
wandb_name: 'meta-codellama-34b-python-Score8192V4'                            
wandb_log_model:


gradient_accumulation_steps: 4
micro_batch_size: 1
num_epochs: 14
optimizer: adamw_torch
lr_scheduler: cosine
learning_rate: 0.0002


train_on_inputs: false
group_by_length: false
bf16: true
fp16:
tf32: false
hub_model_id: afrias5/meta-codellama-34b-python-Score8192V4
gradient_checkpointing: true
early_stopping_patience:
resume_from_checkpoint:
local_rank:
logging_steps: 1
xformers_attention:
flash_attention: false
s2_attention:
logging_steps: 1
warmup_steps: 10
saves_per_epoch: 1
save_total_limit: 16
debug:
deepspeed:
weight_decay: 0.0
fsdp:
deepspeed: deepspeed_configs/zero3_bf16_cpuoffload_all.json
fsdp_config:
special_tokens:
  bos_token: "<s>"
  eos_token: "</s>"
  unk_token: "<unk>"




```

</details><br>

# meta-codellama-34b-python-Score8192V4

This model is a fine-tuned version of [meta-llama/CodeLlama-34b-Python-hf](https://huggingface.co/meta-llama/CodeLlama-34b-Python-hf) on the afrias5/datasetScoreFinal 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: 1
- eval_batch_size: 1
- seed: 42
- distributed_type: multi-GPU
- num_devices: 2
- gradient_accumulation_steps: 4
- total_train_batch_size: 8
- total_eval_batch_size: 2
- optimizer: Use 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: 10
- num_epochs: 14

### Training results



### Framework versions

- PEFT 0.14.0
- Transformers 4.46.3
- Pytorch 2.5.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3