File size: 4,885 Bytes
3e843c0 4b21382 3e843c0 4b21382 3e843c0 4b21382 3e843c0 4b21382 3e843c0 4b21382 3e843c0 4b21382 3e843c0 4b21382 3e843c0 4b21382 3e843c0 4b21382 3e843c0 4b21382 3e843c0 810440c 3e843c0 4b21382 3e843c0 4b21382 3e843c0 4b21382 |
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 |
---
license: apache-2.0
base_model: Qwen/Qwen2-0.5B
tags:
- generated_from_trainer
model-index:
- name: 0.5b out
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: `0.4.1`
```yaml
base_model: Qwen/Qwen2-0.5B
model_type: AutoModelForCausalLM
tokenizer_type: AutoTokenizer
# load_in_4bit: true
chat_template: chatml
datasets:
- path: /workspace/datasets/dolphin201-sharegpt2.jsonl
type: sharegpt
conversation: chatml
- path: /workspace/datasets/SystemChat_sharegpt.jsonl
type: sharegpt
conversation: chatml
# - path: /workspace/datasets/SystemChat_multilingual_sharegpt.jsonl
# type: sharegpt
# conversation: chatml
# - path: /workspace/datasets/SystemChat-2.0-Arabic/SystemChatArabic_sharegpt.jsonl
# type: sharegpt
# conversation: chatml
# - path: /workspace/datasets/dolphin-coder-translate-sharegpt2.jsonl
# type: sharegpt
# conversation: chatml
# - path: /workspace/datasets/dolphin-coder-codegen-sharegpt2.jsonl
# type: sharegpt
# conversation: chatml
# - path: /workspace/datasets/m-a-p_Code-Feedback-sharegpt-unfiltered.jsonl
# type: sharegpt
# conversation: chatml
# - path: /workspace/datasets/m-a-p_CodeFeedback-Filtered-Instruction-sharegpt-unfiltered.jsonl
# type: sharegpt
# conversation: chatml
- path: /workspace/datasets/not_samantha_norefusals.jsonl
type: sharegpt
conversation: chatml
- path: /workspace/datasets/Orca-Math-resort-unfiltered.jsonl
type: sharegpt
# conversation: chatml
# - path: /workspace/datasets/agent_instruct_react_unfiltered.jsonl
# type: sharegpt
# conversation: chatml
# - path: /workspace/datasets/toolbench_instruct_j1s1_3k_unfiltered.jsonl
# type: sharegpt
# conversation: chatml
# - path: /workspace/datasets/toolbench_negative_unfiltered.jsonl
# type: sharegpt
# conversation: chatml
# - path: /workspace/datasets/toolbench_react_10p_unfiltered.jsonl
# type: sharegpt
# conversation: chatml
# - path: /workspace/datasets/toolbench_tflan_cot_30p_unfiltered.jsonl
# type: sharegpt
# conversation: chatml
- path: /workspace/datasets/openhermes200k_unfiltered.jsonl
type: sharegpt
conversation: chatml
dataset_prepared_path: last_run_prepared
val_set_size: 0.03
output_dir: 0.5b out
sequence_len: 16384
sample_packing: true
pad_to_sequence_len: true
# adapter: qlora
# lora_r: 16
# lora_alpha: 32
# lora_dropout: 0.05
# lora_target_modules:
# - q_proj
# - k_proj
# - v_proj
# - o_proj
# - gate_proj
# - up_proj
# - down_proj
wandb_project: 2.9.3-qwen-2.9.3-qwen2-0.5b
# wandb_entity: oaaic
# wandb_watch:
# wandb_name:
# wandb_log_model:
gradient_accumulation_steps: 4
micro_batch_size: 1
num_epochs: 3
optimizer: adamw_8bit
lr_scheduler: constant
learning_rate: 1e-4
# max_grad_norm: 1.0
train_on_inputs: false
group_by_length: false
bf16: true
tf32: false
gradient_checkpointing: true
gradient_checkpointing_kwargs:
use_reentrant: true
logging_steps: 1
flash_attention: true
deepspeed: /workspace/axolotl/deepspeed_configs/zero3_bf16.json
warmup_steps: 10
# evals_per_epoch: 2
saves_per_epoch: 2
save_total_limit: 2
weight_decay: 0.1
special_tokens:
eos_token: <|im_end|>
```
</details><br>
# 0.5b out
This model is a fine-tuned version of [Qwen/Qwen2-0.5B](https://huggingface.co/Qwen/Qwen2-0.5B) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9948
## 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: 0.0001
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- total_eval_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant
- lr_scheduler_warmup_steps: 10
- num_epochs: 3
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 1.0145 | 1.0111 | 933 | 1.0237 |
| 0.9716 | 2.0116 | 1867 | 0.9972 |
| 0.8939 | 2.9743 | 2766 | 0.9948 |
### Framework versions
- Transformers 4.41.1
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
|