Model save
Browse files- .gitattributes +1 -0
- README.md +70 -0
- all_results.json +9 -0
- config.json +29 -0
- generation_config.json +7 -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 +261 -0
- runs/Jul10_14-15-42_ale-distillm-2-0-0/events.out.tfevents.1720617518.ale-distillm-2-0-0.3262.0 +3 -0
- runs/Jul10_14-20-15_ale-distillm-2-0-0/events.out.tfevents.1720617637.ale-distillm-2-0-0.3463.0 +3 -0
- runs/Jul10_15-20-59_ale-distillm-8-0-0/events.out.tfevents.1720621443.ale-distillm-8-0-0.2231.0 +3 -0
- special_tokens_map.json +34 -0
- tokenizer.json +3 -0
- tokenizer_config.json +70 -0
- train_results.json +9 -0
- trainer_state.json +1326 -0
- training_args.bin +3 -0
.gitattributes
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@@ -33,3 +33,4 @@ saved_model/**/* 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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*.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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README.md
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---
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license: gemma
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base_model: google/gemma-7b
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tags:
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- trl
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- sft
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- generated_from_trainer
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datasets:
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- generator
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model-index:
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- name: zephyr-7b-gemma-sft
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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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[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](None)
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# zephyr-7b-gemma-sft
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This model is a fine-tuned version of [google/gemma-7b](https://huggingface.co/google/gemma-7b) on the generator dataset.
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It achieves the following results on the evaluation set:
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- Loss: 1.0774
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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: 2e-05
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- train_batch_size: 4
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- eval_batch_size: 4
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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: 4
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- total_train_batch_size: 128
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- total_eval_batch_size: 32
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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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- num_epochs: 3
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### Training results
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| Training Loss | Epoch | Step | Validation Loss |
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|:-------------:|:------:|:----:|:---------------:|
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| 0.9246 | 0.9983 | 299 | 1.0268 |
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| 0.7512 | 2.0 | 599 | 1.0420 |
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| 0.4573 | 2.9950 | 897 | 1.0774 |
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### Framework versions
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- Transformers 4.42.3
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- Pytorch 2.3.1+cu121
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- Datasets 2.20.0
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- Tokenizers 0.19.1
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all_results.json
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{
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"epoch": 2.994991652754591,
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"total_flos": 246978202042368.0,
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"train_loss": 0.8908544659880359,
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"train_runtime": 5202.4388,
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"train_samples": 9500,
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"train_samples_per_second": 22.101,
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"train_steps_per_second": 0.172
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}
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config.json
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"architectures": [
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"GemmaForCausalLM"
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],
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"attention_bias": false,
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"attention_dropout": 0.0,
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"bos_token_id": 2,
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"eos_token_id": 1,
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"head_dim": 256,
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"hidden_act": "gelu",
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"hidden_activation": "gelu_pytorch_tanh",
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"hidden_size": 3072,
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"initializer_range": 0.02,
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"intermediate_size": 24576,
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"max_position_embeddings": 8192,
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"model_type": "gemma",
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"num_attention_heads": 16,
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"num_hidden_layers": 28,
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"num_key_value_heads": 16,
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"rms_norm_eps": 1e-06,
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"rope_scaling": null,
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"torch_dtype": "bfloat16",
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"use_cache": false,
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"vocab_size": 256000
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}
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generation_config.json
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}
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