juyongjiang
commited on
Commit
•
9d869fd
1
Parent(s):
e2dc056
update model checkpoint
Browse files- README.md +19 -22
- adapter_config.json +0 -5
- adapter_model.safetensors +2 -2
- all_results.json +11 -11
- config.json +2 -2
- eval_results.json +5 -5
- runs/Jun13_05-28-24_gpu1-2/events.out.tfevents.1718227795.gpu1-2.1098203.0 +3 -0
- runs/Jun13_05-28-24_gpu1-2/events.out.tfevents.1718227846.gpu1-2.1098203.1 +3 -0
- runs/Jun13_05-43-12_gpu1-2/events.out.tfevents.1718228630.gpu1-2.1115325.0 +3 -0
- runs/Jun13_05-43-12_gpu1-2/events.out.tfevents.1718228682.gpu1-2.1115325.1 +3 -0
- train_results.json +7 -7
- trainer_state.json +87 -143
- training_args.bin +1 -1
README.md
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---
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license: gemma
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library_name: peft
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tags:
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- alignment-handbook
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- trl
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- sft
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- generated_from_trainer
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base_model: google/gemma-7b
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datasets:
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- llama-duo/synth_summarize_dataset_dedup
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model-index:
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- name: gemma7b-summarize-gpt4o-1k
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results: []
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This model is a fine-tuned version of [google/gemma-7b](https://huggingface.co/google/gemma-7b) on the llama-duo/synth_summarize_dataset_dedup dataset.
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It achieves the following results on the evaluation set:
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- Loss:
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## Model description
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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: 4
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- eval_batch_size:
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- seed: 42
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- distributed_type: multi-GPU
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- num_devices:
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- gradient_accumulation_steps: 2
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- total_train_batch_size:
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- total_eval_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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### Training results
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| Training Loss | Epoch
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### Framework versions
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- PEFT 0.10.0
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- Transformers 4.40.0
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- Pytorch 2.2
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- Datasets 2.18.0
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- Tokenizers 0.19.1
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---
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library_name: peft
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tags:
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- alignment-handbook
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- generated_from_trainer
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datasets:
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- llama-duo/synth_summarize_dataset_dedup
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+
base_model: google/gemma-7b
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model-index:
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- name: gemma7b-summarize-gpt4o-1k
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results: []
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This model is a fine-tuned version of [google/gemma-7b](https://huggingface.co/google/gemma-7b) on the llama-duo/synth_summarize_dataset_dedup dataset.
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It achieves the following results on the evaluation set:
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- Loss: 8.6199
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## Model description
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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: 4
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- eval_batch_size: 2
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- seed: 42
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- distributed_type: multi-GPU
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- num_devices: 8
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- gradient_accumulation_steps: 2
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- total_train_batch_size: 64
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- total_eval_batch_size: 16
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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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### Training results
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| Training Loss | Epoch | Step | Validation Loss |
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|:-------------:|:-----:|:----:|:---------------:|
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| 45.5656 | 1.0 | 2 | 16.5046 |
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| 45.5656 | 2.0 | 4 | 14.2000 |
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| 35.6654 | 3.0 | 6 | 12.9944 |
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| 35.6654 | 4.0 | 8 | 11.5695 |
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| 22.2461 | 5.0 | 10 | 10.3065 |
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| 22.2461 | 6.0 | 12 | 9.3645 |
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| 22.2461 | 7.0 | 14 | 8.9071 |
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| 19.7508 | 8.0 | 16 | 8.6934 |
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| 19.7508 | 9.0 | 18 | 8.6287 |
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| 19.172 | 10.0 | 20 | 8.6199 |
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### Framework versions
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- PEFT 0.10.0
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- Transformers 4.40.0
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- Pytorch 2.1.2+cu121
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- Datasets 2.18.0
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- Tokenizers 0.19.1
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adapter_config.json
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"rank_pattern": {},
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"revision": null,
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"target_modules": [
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"k_proj",
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"up_proj",
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"o_proj",
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"down_proj",
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"q_proj",
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"gate_proj",
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"v_proj"
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],
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"task_type": "CAUSAL_LM",
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"rank_pattern": {},
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"revision": null,
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"target_modules": [
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"q_proj",
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"task_type": "CAUSAL_LM",
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adapter_model.safetensors
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all_results.json
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config.json
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"_load_in_4bit": true,
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"_load_in_8bit": false,
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"bnb_4bit_compute_dtype": "bfloat16",
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"bnb_4bit_quant_type": "nf4",
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"_load_in_4bit": true,
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