indiejoseph
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Browse files- README.md +11 -11
- all_results.json +6 -6
- config.json +4 -4
- generation_config.json +1 -1
- input_embeddings.pt +3 -0
- model-00001-of-00003.safetensors +2 -2
- model-00003-of-00003.safetensors +2 -2
- model.safetensors.index.json +1 -1
- output_embeddings.pt +3 -0
- tokenizer.json +0 -0
- tokenizer.model +2 -2
- train_results.json +6 -6
- trainer_log.jsonl +0 -0
- trainer_state.json +0 -0
- training_args.bin +2 -2
- training_loss.png +0 -0
README.md
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base_model: 01-ai/Yi-1.5-6B
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tags:
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- llama-factory
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-
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- generated_from_trainer
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model-index:
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- name:
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results: []
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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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This model is a fine-tuned version of [01-ai/Yi-1.5-6B](https://huggingface.co/01-ai/Yi-1.5-6B) on the
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## Model description
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate:
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- train_batch_size:
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- eval_batch_size: 8
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- seed: 42
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- gradient_accumulation_steps:
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- total_train_batch_size:
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: cosine
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- lr_scheduler_warmup_ratio: 0.1
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### Framework versions
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- Transformers 4.41.
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- Pytorch 2.
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- Datasets 2.
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- Tokenizers 0.19.1
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base_model: 01-ai/Yi-1.5-6B
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tags:
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- llama-factory
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- freeze
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- generated_from_trainer
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model-index:
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- name: yi-1.5-6b-yub-vocab-expanded
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results: []
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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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# yi-1.5-6b-yub-vocab-expanded
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This model is a fine-tuned version of [01-ai/Yi-1.5-6B](https://huggingface.co/01-ai/Yi-1.5-6B) undergone layers freezeing learning on the 300m tokens Cantonese dataset, in order to train a new words embedding in the expanded vocab. This model has not been continued pre-trainined, therefore it is not recommended to be used for further pre-training.
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## Model description
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 0.0002
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- train_batch_size: 8
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- eval_batch_size: 8
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- seed: 42
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- gradient_accumulation_steps: 16
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- total_train_batch_size: 128
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: cosine
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- lr_scheduler_warmup_ratio: 0.1
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### Framework versions
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- Transformers 4.41.2
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- Pytorch 2.1.1+cu121
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- Datasets 2.15.0
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- Tokenizers 0.19.1
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all_results.json
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"train_loss": 2.
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}
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{
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"epoch": 0.9996843204390374,
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"total_flos": 1.1741952995733012e+19,
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"train_loss": 2.4089672912015,
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"train_runtime": 234538.8638,
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"train_samples_per_second": 1.405,
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"train_steps_per_second": 0.011
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}
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config.json
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{
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"_name_or_path": "
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"architectures": [
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"LlamaForCausalLM"
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],
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"rope_theta": 5000000.0,
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"tie_word_embeddings": false,
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"torch_dtype": "bfloat16",
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"transformers_version": "4.41.
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"use_cache": false,
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"vocab_size":
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}
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{
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"_name_or_path": "/notebooks/cantonese/llm/models/cantonesellm-cpt-freeze-stag4",
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"architectures": [
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"LlamaForCausalLM"
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"rope_theta": 5000000.0,
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"tie_word_embeddings": false,
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"torch_dtype": "bfloat16",
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"transformers_version": "4.41.2",
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"use_cache": false,
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"vocab_size": 64960
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}
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generation_config.json
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"bos_token_id": 1,
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"eos_token_id": 2,
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"pad_token_id": 0,
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"transformers_version": "4.41.
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"transformers_version": "4.41.2"
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}
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input_embeddings.pt
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model.safetensors.index.json
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output_embeddings.pt
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tokenizer.json
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tokenizer.model
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train_results.json
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trainer_log.jsonl
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trainer_state.json
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training_args.bin
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training_loss.png
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