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--- |
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base_model: alpindale/Mistral-7B-v0.2-hf |
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language: |
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- en |
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license: apache-2.0 |
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datasets: |
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- cognitivecomputations/dolphin |
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- cognitivecomputations/dolphin-coder |
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- cognitivecomputations/samantha-data |
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- jondurbin/airoboros-2.2.1 |
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- teknium/openhermes-2.5 |
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- m-a-p/Code-Feedback |
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- m-a-p/CodeFeedback-Filtered-Instruction |
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--- |
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# Dolphin 2.8 Mistral 7b v0.2 🐬 |
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By Eric Hartford and Cognitive Computations |
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Discord: https://discord.gg/8fbBeC7ZGx |
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<img src="https://cdn-uploads.huggingface.co/production/uploads/63111b2d88942700629f5771/ldkN1J0WIDQwU4vutGYiD.png" width="600" /> |
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My appreciation for the sponsors of Dolphin 2.8: |
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- [Crusoe Cloud](https://crusoe.ai/) - provided excellent on-demand 10xL40S node |
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- [Winston Sou](https://twitter.com/WinsonDabbles) - Along with a generous anonymous sponsor, donated a massive personally owned compute resource! |
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- [Abacus AI](https://abacus.ai/) - my employer and partner in many things. |
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This model is based on [Mistral-7b-v0.2](https://huggingface.co/alpindale/Mistral-7B-v0.2-hf) a new base model released by MistralAI on March 23, 2024 but they have not yet published on HuggingFace. Thanks to @alpindale for converting / publishing. |
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The base model has 32k context, and the full-weights fine-tune was with 16k sequence lengths. |
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It took 3 days on 10x L40S provided by [Crusoe Cloud](https://crusoe.ai/) |
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Dolphin-2.8 has a variety of instruction, conversational, and coding skills. |
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This model is uncensored. I have filtered the dataset to remove alignment and bias. This makes the model more compliant. You are advised to implement your own alignment layer before exposing the model as a service. It will be highly compliant to any requests, even unethical ones. Please read my blog post about uncensored models. https://erichartford.com/uncensored-models You are responsible for any content you create using this model. Enjoy responsibly. |
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# Evals |
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``` |
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{ |
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"arc_challenge": { |
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"acc,none": 0.5921501706484642, |
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"acc_stderr,none": 0.014361097288449701, |
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"acc_norm,none": 0.6339590443686007, |
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"acc_norm_stderr,none": 0.014077223108470139 |
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}, |
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"gsm8k": { |
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"exact_match,strict-match": 0.4783927217589083, |
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"exact_match_stderr,strict-match": 0.013759618667051773, |
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"exact_match,flexible-extract": 0.5367702805155421, |
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"exact_match_stderr,flexible-extract": 0.013735191956468648 |
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}, |
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"hellaswag": { |
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"acc,none": 0.6389165504879506, |
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"acc_stderr,none": 0.004793330525656218, |
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"acc_norm,none": 0.8338976299541924, |
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"acc_norm_stderr,none": 0.00371411888431746 |
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}, |
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"mmlu": { |
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"acc,none": 0.6122347243982339, |
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"acc_stderr,none": 0.003893774654142997 |
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}, |
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"truthfulqa_mc2": { |
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"acc,none": 0.5189872652778472, |
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"acc_stderr,none": 0.014901128316426086 |
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}, |
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"winogrande": { |
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"acc,none": 0.7971586424625099, |
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"acc_stderr,none": 0.011301439925936643 |
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} |
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} |
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``` |
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[<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) |
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<details><summary>See axolotl config</summary> |
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axolotl version: `0.4.0` |
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```yaml |
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base_model: alpindale/Mistral-7B-v0.2-hf |
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model_type: MistralForCausalLM |
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tokenizer_type: LlamaTokenizer |
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is_mistral_derived_model: true |
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load_in_8bit: false |
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load_in_4bit: false |
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strict: false |
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datasets: |
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- path: /workspace/datasets/dolphin201-sharegpt2.jsonl |
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type: sharegpt |
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- path: /workspace/datasets/dolphin-coder-translate-sharegpt2.jsonl |
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type: sharegpt |
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- path: /workspace/datasets/dolphin-coder-codegen-sharegpt2.jsonl |
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type: sharegpt |
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- path: /workspace/datasets/m-a-p_Code-Feedback-sharegpt.jsonl |
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type: sharegpt |
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- path: /workspace/datasets/m-a-p_CodeFeedback-Filtered-Instruction-sharegpt.jsonl |
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type: sharegpt |
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- path: /workspace/datasets/not_samantha_norefusals.jsonl |
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type: sharegpt |
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- path: /workspace/datasets/openhermes2_5-sharegpt.jsonl |
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type: sharegpt |
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chat_template: chatml |
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dataset_prepared_path: last_run_prepared |
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val_set_size: 0.001 |
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output_dir: /workspace/dolphin-2.8-mistral-7b |
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sequence_len: 16384 |
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sample_packing: true |
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pad_to_sequence_len: true |
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wandb_project: dolphin |
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wandb_entity: |
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wandb_watch: |
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wandb_run_id: |
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wandb_log_model: |
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gradient_accumulation_steps: 8 |
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micro_batch_size: 3 |
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num_epochs: 4 |
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adam_beta2: 0.95 |
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adam_epsilon: 0.00001 |
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max_grad_norm: 1.0 |
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lr_scheduler: cosine |
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learning_rate: 0.000005 |
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optimizer: adamw_bnb_8bit |
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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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gradient_checkpointing: true |
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gradient_checkpointing_kwargs: |
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use_reentrant: true |
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early_stopping_patience: |
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resume_from_checkpoint: |
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local_rank: |
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logging_steps: 1 |
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xformers_attention: |
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flash_attention: true |
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warmup_steps: 10 |
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eval_steps: 73 |
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eval_table_size: |
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eval_table_max_new_tokens: |
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eval_sample_packing: false |
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saves_per_epoch: |
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save_steps: 73 |
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save_total_limit: 2 |
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debug: |
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deepspeed: deepspeed_configs/zero3_bf16.json |
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weight_decay: 0.1 |
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fsdp: |
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fsdp_config: |
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special_tokens: |
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eos_token: "<|im_end|>" |
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tokens: |
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- "<|im_start|>" |
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``` |
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</details><br> |
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# workspace/dolphin-2.8-mistral-7b |
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This model is a fine-tuned version of [alpindale/Mistral-7B-v0.2-hf](https://huggingface.co/alpindale/Mistral-7B-v0.2-hf) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4828 |
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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: 5e-06 |
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- train_batch_size: 3 |
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- eval_batch_size: 3 |
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- seed: 42 |
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- distributed_type: multi-GPU |
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- num_devices: 10 |
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- gradient_accumulation_steps: 8 |
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- total_train_batch_size: 240 |
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- total_eval_batch_size: 30 |
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- optimizer: Adam with betas=(0.9,0.95) and epsilon=1e-05 |
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- lr_scheduler_type: cosine |
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- lr_scheduler_warmup_steps: 10 |
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- num_epochs: 4 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:-----:|:----:|:---------------:| |
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| 1.1736 | 0.0 | 1 | 1.0338 | |
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| 0.6106 | 0.36 | 73 | 0.5439 | |
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| 0.5766 | 0.72 | 146 | 0.5171 | |
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| 0.5395 | 1.06 | 219 | 0.5045 | |
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| 0.5218 | 1.42 | 292 | 0.4976 | |
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| 0.5336 | 1.78 | 365 | 0.4915 | |
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| 0.5018 | 2.13 | 438 | 0.4885 | |
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| 0.5113 | 2.48 | 511 | 0.4856 | |
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| 0.5066 | 2.84 | 584 | 0.4838 | |
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| 0.4967 | 3.19 | 657 | 0.4834 | |
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| 0.4956 | 3.55 | 730 | 0.4830 | |
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| 0.5026 | 3.9 | 803 | 0.4828 | |
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### Framework versions |
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- Transformers 4.40.0.dev0 |
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- Pytorch 2.2.1+cu121 |
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- Datasets 2.18.0 |
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- Tokenizers 0.15.0 |
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# Quants |
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- [dagbs/-GGUF](https://huggingface.co/dagbs/dolphin-2.8-mistral-7b-v02-GGUF) |
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- [bartowski/ExLlamaV2](https://huggingface.co/bartowski/dolphin-2.8-mistral-7b-v02-exl2) |
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- [solidrust/AWQ](https://huggingface.co/solidrust/dolphin-2.8-mistral-7b-v02-AWQ) |
