File size: 7,650 Bytes
d46ca7a
 
8133450
 
 
 
 
 
 
 
 
 
 
2874cb0
 
 
 
 
 
 
 
 
 
 
 
 
d46ca7a
 
8133450
 
 
 
6e0cd64
 
8133450
 
 
 
 
 
 
 
 
 
d58483a
 
 
8133450
 
 
813b7d8
 
 
75c91d1
8133450
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
d46ca7a
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
2b604e4
 
 
 
f7de8cf
 
af7387b
 
 
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
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
---
base_model: alpindale/Mistral-7B-v0.2-hf
language:
- en
license: apache-2.0
datasets:
- cognitivecomputations/dolphin
- cognitivecomputations/dolphin-coder
- cognitivecomputations/samantha-data
- jondurbin/airoboros-2.2.1
- teknium/openhermes-2.5
- m-a-p/Code-Feedback
- m-a-p/CodeFeedback-Filtered-Instruction
model-index:
- name: dolphin-2.8-mistral-7b-v02
  results:
  - task:
      type: text-generation
    dataset:
      type: openai_humaneval
      name: HumanEval
    metrics:
    - name: pass@1
      type: pass@1
      value: 0.469
      verified: false
---

# Dolphin 2.8 Mistral 7b v0.2 🐬

By Eric Hartford and Cognitive Computations

[![Discord](https://img.shields.io/discord/1156064224225808488?logo=Discord&logoColor=%23ffffff&label=Discord&link=https%3A%2F%2Fdiscord.gg%2FtCMkMDDHwm)](https://discord.gg/cognitivecomputations)
Discord: https://discord.gg/cognitivecomputations

<img src="https://cdn-uploads.huggingface.co/production/uploads/63111b2d88942700629f5771/ldkN1J0WIDQwU4vutGYiD.png" width="600" />

My appreciation for the sponsors of Dolphin 2.8:
- [Crusoe Cloud](https://crusoe.ai/) - provided excellent on-demand 10xL40S node
- [Winston Sou](https://twitter.com/WinsonDabbles) - Along with a generous anonymous sponsor, donated a massive personally owned compute resource!
- [Abacus AI](https://abacus.ai/) - my employer and partner in many things.

This model is based on [Mistral-7b-v0.2](https://huggingface.co/alpindale/Mistral-7B-v0.2-hf) a new base model released by MistralAI on March 23, 2024 but they have not yet published on HuggingFace.  Thanks to @alpindale for converting / publishing.

The base model has 32k context, and the full-weights fine-tune was with 16k sequence lengths.

It took 3 days on 10x L40S provided by [Crusoe Cloud](https://crusoe.ai/)

Dolphin-2.8 has a variety of instruction, conversational, and coding skills.

Dolphin is uncensored. I have filtered the dataset to remove alignment and bias. This makes the model more compliant. You are advised to implement your own alignment layer before exposing the model as a service. It will be highly compliant to any requests, even unethical ones. Please read my blog post about uncensored models. https://erichartford.com/uncensored-models You are responsible for any content you create using this model. Enjoy responsibly.

Dolphin is licensed Apache 2.0.  I grant permission for any use including commercial.  Dolphin was trained on data generated from GPT4 among other models.

# Evals

```
{
  "arc_challenge": {
    "acc,none": 0.5921501706484642,
    "acc_stderr,none": 0.014361097288449701,
    "acc_norm,none": 0.6339590443686007,
    "acc_norm_stderr,none": 0.014077223108470139
  },
  "gsm8k": {
    "exact_match,strict-match": 0.4783927217589083,
    "exact_match_stderr,strict-match": 0.013759618667051773,
    "exact_match,flexible-extract": 0.5367702805155421,
    "exact_match_stderr,flexible-extract": 0.013735191956468648
  },
  "hellaswag": {
    "acc,none": 0.6389165504879506,
    "acc_stderr,none": 0.004793330525656218,
    "acc_norm,none": 0.8338976299541924,
    "acc_norm_stderr,none": 0.00371411888431746
  },
  "mmlu": {
    "acc,none": 0.6122347243982339,
    "acc_stderr,none": 0.003893774654142997
  },
  "truthfulqa_mc2": {
    "acc,none": 0.5189872652778472,
    "acc_stderr,none": 0.014901128316426086
  },
  "winogrande": {
    "acc,none": 0.7971586424625099,
    "acc_stderr,none": 0.011301439925936643
  }
}
```

[<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: alpindale/Mistral-7B-v0.2-hf
model_type: MistralForCausalLM
tokenizer_type: LlamaTokenizer
is_mistral_derived_model: true

load_in_8bit: false
load_in_4bit: false
strict: false

datasets:
  - path: /workspace/datasets/dolphin201-sharegpt2.jsonl
    type: sharegpt
  - path: /workspace/datasets/dolphin-coder-translate-sharegpt2.jsonl
    type: sharegpt
  - path: /workspace/datasets/dolphin-coder-codegen-sharegpt2.jsonl
    type: sharegpt
  - path: /workspace/datasets/m-a-p_Code-Feedback-sharegpt.jsonl
    type: sharegpt
  - path: /workspace/datasets/m-a-p_CodeFeedback-Filtered-Instruction-sharegpt.jsonl
    type: sharegpt
  - path: /workspace/datasets/not_samantha_norefusals.jsonl
    type: sharegpt
  - path: /workspace/datasets/openhermes2_5-sharegpt.jsonl
    type: sharegpt

chat_template: chatml

dataset_prepared_path: last_run_prepared
val_set_size: 0.001
output_dir: /workspace/dolphin-2.8-mistral-7b

sequence_len: 16384
sample_packing: true
pad_to_sequence_len: true

wandb_project: dolphin
wandb_entity:
wandb_watch:
wandb_run_id:
wandb_log_model:

gradient_accumulation_steps: 8
micro_batch_size: 3
num_epochs: 4
adam_beta2: 0.95
adam_epsilon: 0.00001
max_grad_norm: 1.0
lr_scheduler: cosine
learning_rate: 0.000005
optimizer: adamw_bnb_8bit

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

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

warmup_steps: 10

eval_steps: 73
eval_table_size:
eval_table_max_new_tokens:
eval_sample_packing: false
saves_per_epoch: 
save_steps: 73
save_total_limit: 2
debug:
deepspeed: deepspeed_configs/zero3_bf16.json
weight_decay: 0.1
fsdp:
fsdp_config:
special_tokens:
  eos_token: "<|im_end|>"
tokens:
  - "<|im_start|>"

```

</details><br>

# workspace/dolphin-2.8-mistral-7b

This model is a fine-tuned version of [alpindale/Mistral-7B-v0.2-hf](https://huggingface.co/alpindale/Mistral-7B-v0.2-hf) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4828

## 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: 5e-06
- train_batch_size: 3
- eval_batch_size: 3
- seed: 42
- distributed_type: multi-GPU
- num_devices: 10
- gradient_accumulation_steps: 8
- total_train_batch_size: 240
- total_eval_batch_size: 30
- optimizer: Adam with betas=(0.9,0.95) and epsilon=1e-05
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 10
- num_epochs: 4

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 1.1736        | 0.0   | 1    | 1.0338          |
| 0.6106        | 0.36  | 73   | 0.5439          |
| 0.5766        | 0.72  | 146  | 0.5171          |
| 0.5395        | 1.06  | 219  | 0.5045          |
| 0.5218        | 1.42  | 292  | 0.4976          |
| 0.5336        | 1.78  | 365  | 0.4915          |
| 0.5018        | 2.13  | 438  | 0.4885          |
| 0.5113        | 2.48  | 511  | 0.4856          |
| 0.5066        | 2.84  | 584  | 0.4838          |
| 0.4967        | 3.19  | 657  | 0.4834          |
| 0.4956        | 3.55  | 730  | 0.4830          |
| 0.5026        | 3.9   | 803  | 0.4828          |


### Framework versions

- Transformers 4.40.0.dev0
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.0


# Quants

- [dagbs/-GGUF](https://huggingface.co/dagbs/dolphin-2.8-mistral-7b-v02-GGUF)

- [bartowski/ExLlamaV2](https://huggingface.co/bartowski/dolphin-2.8-mistral-7b-v02-exl2)

- [solidrust/AWQ](https://huggingface.co/solidrust/dolphin-2.8-mistral-7b-v02-AWQ)