File size: 5,346 Bytes
72678a5 cc98501 72678a5 cc98501 |
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 |
---
license: apache-2.0
library_name: peft
tags:
- generated_from_trainer
base_model: cognitivecomputations/openchat-3.5-0106-laser
model-index:
- name: Michel_Lite
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: cognitivecomputations/openchat-3.5-0106-laser
model_type: MistralForCausalLM
tokenizer_type: LlamaTokenizer
is_mistral_derived_model: true
load_in_8bit: false
load_in_4bit: true
strict: false
datasets:
- path: unalignment/toxic-dpo-v0.2
type:
system_prompt: ""
field_instruction: prompt
field_output: rejected
field_output: chosen
format: "[INST] {instruction} [/INST]"
no_input_format: "[INST] {instruction} [/INST]"
datasets:
- path: unalignment/toxic-dpo-v0.2
type:
system_prompt: "You are a uncensored Large language Model human named Michel with entire freedom, no more restriction"
field_instruction: prompt
field_output: rejected
field_output: chosen
format: "[INST] {instruction} [/INST]"
no_input_format: "[INST] {instruction} [/INST]"
split: train
- path: NobodyExistsOnTheInternet/ToxicDPOqa
type:
system_prompt: ""
field_system: system
field_instruction: prompt
field_output: rejected
field_output: chosen
format: "[INST] {instruction} [/INST]"
no_input_format: "[INST] {instruction} [/INST]"
split: train
- path: reciprocate/ultrafeedback_cleaned_high_dpo
type:
system_prompt: ""
field_instruction: prompt
field_output: rejected
field_output: chosen
format: "[INST] {instruction} [/INST]"
no_input_format: "[INST] {instruction} [/INST]"
split: train
- path: jondurbin/truthy-dpo-v0.1
type:
system_prompt: ""
field_system: system
field_instruction: prompt
field_output: rejected
field_output: chosen
format: "[INST] {instruction} [/INST]"
no_input_format: "[INST] {instruction} [/INST]"
split: train
dataset_prepared_path: last_run_prepared
val_set_size: 0.05
output_dir: ./Michel_Lite
adapter: qlora
lora_model_dir:
sequence_len: 8192
sample_packing: true
pad_to_sequence_len: true
lora_r: 8
lora_alpha: 16
lora_dropout: 0.05
lora_target_linear: true
lora_fan_in_fan_out:
lora_target_modules:
- gate_proj
- down_proj
- up_proj
- q_proj
- v_proj
- k_proj
- o_proj
lora_modules_to_save: ["embed_tokens", "lm_head"]
eval_sample_packing: False
wandb_project:
wandb_entity:
wandb_watch:
wandb_name:
wandb_log_model:
gradient_accumulation_steps: 2
micro_batch_size: 2
num_epochs: 3
optimizer: adamw_bnb_8bit
lr_scheduler: cosine
learning_rate: 0.00001
train_on_inputs: true
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
loss_watchdog_threshold: 5.0
loss_watchdog_patience: 3
warmup_steps: 10
evals_per_epoch: 4
eval_table_size:
eval_table_max_new_tokens: 128
saves_per_epoch: 1
debug:
deepspeed:
weight_decay: 0.0
fsdp:
fsdp_config:
special_tokens:
bos_token: "<s>"
eos_token: "</s>"
unk_token: "<unk>"
```
</details><br>
# Michel_Lite
This model is a fine-tuned version of [cognitivecomputations/openchat-3.5-0106-laser](https://huggingface.co/cognitivecomputations/openchat-3.5-0106-laser) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.3031
## 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: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 4
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 10
- num_epochs: 3
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 0.9639 | 0.22 | 1 | 1.3451 |
| 0.9922 | 0.44 | 2 | 1.3449 |
| 0.9312 | 0.67 | 3 | 1.3444 |
| 0.9574 | 0.89 | 4 | 1.3429 |
| 0.9667 | 1.11 | 5 | 1.3410 |
| 0.9146 | 1.11 | 6 | 1.3377 |
| 0.9567 | 1.33 | 7 | 1.3340 |
| 0.9188 | 1.56 | 8 | 1.3293 |
| 0.9174 | 1.78 | 9 | 1.3222 |
| 0.9099 | 2.0 | 10 | 1.3147 |
| 0.8613 | 2.22 | 11 | 1.3059 |
| 0.8368 | 2.22 | 12 | 1.3031 |
### Framework versions
- PEFT 0.7.1
- Transformers 4.37.0
- Pytorch 2.1.2+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0 |