Training in progress, epoch 2
Browse files- .gitattributes +1 -0
- .ipynb_checkpoints/Untitled-checkpoint.ipynb +6 -0
- .ipynb_checkpoints/Untitled1-checkpoint.ipynb +6 -0
- README.md +151 -0
- Untitled.ipynb +6 -0
- Untitled1.ipynb +0 -0
- added_tokens.json +24 -0
- config.json +28 -0
- generation_config.json +14 -0
- merges.txt +0 -0
- model-00001-of-00004.safetensors +3 -0
- model-00002-of-00004.safetensors +3 -0
- model-00003-of-00004.safetensors +3 -0
- model-00004-of-00004.safetensors +3 -0
- model.safetensors.index.json +346 -0
- pytorch_model-00001-of-00002.bin +3 -0
- pytorch_model-00002-of-00002.bin +3 -0
- pytorch_model.bin.index.json +346 -0
- special_tokens_map.json +31 -0
- tokenizer.json +3 -0
- tokenizer_config.json +208 -0
- training_args.bin +3 -0
- vocab.json +0 -0
.gitattributes
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*.zip filter=lfs diff=lfs merge=lfs -text
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*.zst filter=lfs diff=lfs merge=lfs -text
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*.zip filter=lfs diff=lfs merge=lfs -text
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*.zst filter=lfs diff=lfs merge=lfs -text
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*tfevents* filter=lfs diff=lfs merge=lfs -text
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tokenizer.json filter=lfs diff=lfs merge=lfs -text
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.ipynb_checkpoints/Untitled-checkpoint.ipynb
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.ipynb_checkpoints/Untitled1-checkpoint.ipynb
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README.md
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1 |
+
---
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2 |
+
library_name: transformers
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+
license: apache-2.0
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+
base_model: Qwen/Qwen2.5-7B-Instruct
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+
tags:
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+
- axolotl
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+
- generated_from_trainer
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datasets:
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- medalpaca/medical_meadow_medqa
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+
model-index:
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+
- name: sft-qwen-25-7b-instruct
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+
results: []
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+
---
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+
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+
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
|
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+
should probably proofread and complete it, then remove this comment. -->
|
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+
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+
[<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)
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<details><summary>See axolotl config</summary>
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axolotl version: `0.6.0`
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```yaml
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base_model: Qwen/Qwen2.5-7B-Instruct
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+
trust_remote_code: true
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+
model_type: AutoModelForCausalLM
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+
tokenizer_type: AutoTokenizer
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+
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+
load_in_8bit:
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load_in_4bit:
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strict: false
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+
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+
datasets:
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- path: medalpaca/medical_meadow_medqa
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type: alpaca
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+
dataset_prepared_path:
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+
val_set_size: 0.1
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+
output_dir: ./sft-qwen25
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+
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+
sequence_len: 8192
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+
sample_packing: true
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+
eval_sample_packing: true
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+
pad_to_sequence_len: true
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+
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+
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+
wandb_project: sft-qwen-25-7b-instruct
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+
wandb_entity:
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+
wandb_watch:
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+
wandb_name:
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+
wandb_log_model:
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+
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+
gradient_accumulation_steps: 1
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+
micro_batch_size: 1
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+
num_epochs: 1
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+
optimizer: adamw_torch
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+
lr_scheduler: cosine
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+
learning_rate: 0.00001
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+
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+
train_on_inputs: false
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+
group_by_length: false
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+
bf16: true
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+
fp16: false
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+
tf32: false
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+
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+
gradient_checkpointing: true
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+
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+
logging_steps: 1
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+
xformers_attention:
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+
flash_attention: true
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+
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+
warmup_steps:
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+
eval_steps: 10
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+
save_steps: 40
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+
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+
evals_per_epoch:
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+
saves_per_epoch:
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+
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+
debug:
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+
deepspeed: deepspeed_configs/zero2.json
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+
weight_decay:
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+
fsdp:
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+
fsdp_config:
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+
special_tokens:
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+
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+
hub_model_id: neginashz/sft-qwen-25-7b-instruct
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+
hub_strategy: all_checkpoints
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+
early_stopping_patience: 3
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+
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auto_resume_from_checkpoints: true
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```
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</details><br>
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# sft-qwen-25-7b-instruct
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This model is a fine-tuned version of [Qwen/Qwen2.5-7B-Instruct](https://huggingface.co/Qwen/Qwen2.5-7B-Instruct) on the medalpaca/medical_meadow_medqa dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.1055
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 1e-05
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- train_batch_size: 1
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- eval_batch_size: 1
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- seed: 42
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- distributed_type: multi-GPU
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- num_devices: 4
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- total_train_batch_size: 4
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- total_eval_batch_size: 4
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- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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- lr_scheduler_type: cosine
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- lr_scheduler_warmup_steps: 2
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- num_epochs: 1
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### Training results
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| Training Loss | Epoch | Step | Validation Loss |
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|:-------------:|:------:|:----:|:---------------:|
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| 0.1381 | 0.1235 | 10 | 0.1342 |
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| 0.1495 | 0.2469 | 20 | 0.1229 |
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| 0.1215 | 0.3704 | 30 | 0.1246 |
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| 0.1354 | 0.4938 | 40 | 0.1175 |
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| 0.1223 | 0.6173 | 50 | 0.1115 |
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| 0.1068 | 0.7407 | 60 | 0.1101 |
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| 0.1061 | 0.8642 | 70 | 0.1056 |
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| 0.118 | 0.9877 | 80 | 0.1055 |
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### Framework versions
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- Transformers 4.47.0
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- Pytorch 2.5.1+cu124
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- Datasets 3.1.0
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- Tokenizers 0.21.0
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Untitled.ipynb
ADDED
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"metadata": {},
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4 |
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}
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Untitled1.ipynb
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added_tokens.json
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config.json
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{
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"_name_or_path": "Qwen/Qwen2.5-7B-Instruct",
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"architectures": [
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"Qwen2ForCausalLM"
|
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],
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6 |
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|
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"model_type": "qwen2",
|
15 |
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"num_attention_heads": 28,
|
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"num_hidden_layers": 28,
|
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"num_key_value_heads": 4,
|
18 |
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"rms_norm_eps": 1e-06,
|
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"rope_scaling": null,
|
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"rope_theta": 1000000.0,
|
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"sliding_window": null,
|
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"tie_word_embeddings": false,
|
23 |
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"torch_dtype": "bfloat16",
|
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"transformers_version": "4.47.0",
|
25 |
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"use_cache": false,
|
26 |
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"use_sliding_window": false,
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"vocab_size": 152064
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}
|
generation_config.json
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|
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|
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|
merges.txt
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198 |
+
"chat_template": "{%- if tools %}\n {{- '<|im_start|>system\\n' }}\n {%- if messages[0]['role'] == 'system' %}\n {{- messages[0]['content'] }}\n {%- else %}\n {{- 'You are Qwen, created by Alibaba Cloud. You are a helpful assistant.' }}\n {%- endif %}\n {{- \"\\n\\n# Tools\\n\\nYou may call one or more functions to assist with the user query.\\n\\nYou are provided with function signatures within <tools></tools> XML tags:\\n<tools>\" }}\n {%- for tool in tools %}\n {{- \"\\n\" }}\n {{- tool | tojson }}\n {%- endfor %}\n {{- \"\\n</tools>\\n\\nFor each function call, return a json object with function name and arguments within <tool_call></tool_call> XML tags:\\n<tool_call>\\n{\\\"name\\\": <function-name>, \\\"arguments\\\": <args-json-object>}\\n</tool_call><|im_end|>\\n\" }}\n{%- else %}\n {%- if messages[0]['role'] == 'system' %}\n {{- '<|im_start|>system\\n' + messages[0]['content'] + '<|im_end|>\\n' }}\n {%- else %}\n {{- '<|im_start|>system\\nYou are Qwen, created by Alibaba Cloud. You are a helpful assistant.<|im_end|>\\n' }}\n {%- endif %}\n{%- endif %}\n{%- for message in messages %}\n {%- if (message.role == \"user\") or (message.role == \"system\" and not loop.first) or (message.role == \"assistant\" and not message.tool_calls) %}\n {{- '<|im_start|>' + message.role + '\\n' + message.content + '<|im_end|>' + '\\n' }}\n {%- elif message.role == \"assistant\" %}\n {{- '<|im_start|>' + message.role }}\n {%- if message.content %}\n {{- '\\n' + message.content }}\n {%- endif %}\n {%- for tool_call in message.tool_calls %}\n {%- if tool_call.function is defined %}\n {%- set tool_call = tool_call.function %}\n {%- endif %}\n {{- '\\n<tool_call>\\n{\"name\": \"' }}\n {{- tool_call.name }}\n {{- '\", \"arguments\": ' }}\n {{- tool_call.arguments | tojson }}\n {{- '}\\n</tool_call>' }}\n {%- endfor %}\n {{- '<|im_end|>\\n' }}\n {%- elif message.role == \"tool\" %}\n {%- if (loop.index0 == 0) or (messages[loop.index0 - 1].role != \"tool\") %}\n {{- '<|im_start|>user' }}\n {%- endif %}\n {{- '\\n<tool_response>\\n' }}\n {{- message.content }}\n {{- '\\n</tool_response>' }}\n {%- if loop.last or (messages[loop.index0 + 1].role != \"tool\") %}\n {{- '<|im_end|>\\n' }}\n {%- endif %}\n {%- endif %}\n{%- endfor %}\n{%- if add_generation_prompt %}\n {{- '<|im_start|>assistant\\n' }}\n{%- endif %}\n",
|
199 |
+
"clean_up_tokenization_spaces": false,
|
200 |
+
"eos_token": "<|im_end|>",
|
201 |
+
"errors": "replace",
|
202 |
+
"extra_special_tokens": {},
|
203 |
+
"model_max_length": 131072,
|
204 |
+
"pad_token": "<|endoftext|>",
|
205 |
+
"split_special_tokens": false,
|
206 |
+
"tokenizer_class": "Qwen2Tokenizer",
|
207 |
+
"unk_token": null
|
208 |
+
}
|
training_args.bin
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:fa42af68bac583788f8fb87f2da61dcdbbade452bfe4b800777f7bdd5c3bff8d
|
3 |
+
size 8056
|
vocab.json
ADDED
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|
|