Hugging Face's logo

prince-canuma
/
Llama-3-6B-v0.1-adapters

PEFT
Safetensors
llama
Generated from Trainer
4-bit precision
bitsandbytes
Model card Files Community
Llama-3-6B-v0.1-adapters
File size: 3,399 Bytes 
6d5887a
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
e325f55
6d5887a
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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
 
---
library_name: peft
tags:
- generated_from_trainer
base_model: prince-canuma/Llama-3-6B-v0.1
model-index:
- name: llama-3-6b
  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
base_model: prince-canuma/Llama-3-6B-v0
model_type: AutoModelForCausalLM
tokenizer_type: AutoTokenizer

load_in_8bit: false
load_in_4bit: true
strict: false

datasets:
  - path: prince-canuma/fineweb-CC-MAIN-2024-10-1B-en
    type: completion
    split: train
dataset_prepared_path: last_run_prepared
val_set_size: 0.001
output_dir: ./llama-3-6b
save_safetensors: true
adapter: qlora
lora_model_dir:

sequence_len: 8192
sample_packing: false
pad_to_sequence_len: false

lora_r: 128
lora_alpha: 128
lora_dropout: 0.05
lora_target_modules:
lora_target_linear: true
lora_fan_in_fan_out:


wandb_project: llama-3-6b
wandb_entity: 
wandb_watch:
wandb_name:
wandb_log_model:

gradient_accumulation_steps: 8
micro_batch_size: 2
num_epochs: 2
optimizer: paged_adamw_32bit
lr_scheduler: cosine
learning_rate: 2e-4

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

gradient_checkpointing: true
early_stopping_patience:
resume_from_checkpoint:
local_rank:
logging_steps: 1
xformers_attention:
flash_attention: true

warmup_steps: 100
evals_per_epoch: 4
eval_table_size:
save_steps: 4000
debug:
deepspeed:
weight_decay: 0.0
fsdp:
fsdp_config:
special_tokens:
    pad_token: "<|reserved_special_token_0|>"


```

</details><br>

# llama-3-6b

This model is a fine-tuned version of [prince-canuma/Llama-3-6B-v0.1](https://huggingface.co/prince-canuma/Llama-3-6B-v0.1) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 2.4942

## 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: 2
- eval_batch_size: 2
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 8
- total_train_batch_size: 64
- total_eval_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 100
- num_epochs: 2

### Training results

| Training Loss | Epoch | Step  | Validation Loss |
|:-------------:|:-----:|:-----:|:---------------:|
| 7.1562        | 0.0   | 1     | 7.1806          |
| 2.7339        | 0.25  | 5867  | 2.6266          |
| 2.6905        | 0.5   | 11734 | 2.5872          |
| 2.6134        | 0.75  | 17601 | 2.5549          |
| 2.532         | 1.0   | 23468 | 2.5235          |
| 2.5319        | 1.25  | 29335 | 2.5067          |
| 2.3336        | 1.5   | 35202 | 2.4968          |
| 2.3486        | 1.75  | 41069 | 2.4942          |


### Framework versions

- PEFT 0.10.0
- Transformers 4.40.0.dev0
- Pytorch 2.2.0+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0