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+
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+ ---
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+
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+ library_name: transformers
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+ base_model: Dans-DiscountModels/Mistral-NeMo-Minitron-8B-Base-ChatML
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+ tags:
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+ - generated_from_trainer
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+ model-index:
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+ - name: outputs/out
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+ results: []
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+
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+ ---
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+
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+ [![QuantFactory Banner](https://lh7-rt.googleusercontent.com/docsz/AD_4nXeiuCm7c8lEwEJuRey9kiVZsRn2W-b4pWlu3-X534V3YmVuVc2ZL-NXg2RkzSOOS2JXGHutDuyyNAUtdJI65jGTo8jT9Y99tMi4H4MqL44Uc5QKG77B0d6-JfIkZHFaUA71-RtjyYZWVIhqsNZcx8-OMaA?key=xt3VSDoCbmTY7o-cwwOFwQ)](https://hf.co/QuantFactory)
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+
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+
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+ # QuantFactory/Magic_v2_8B-GGUF
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+ This is quantized version of [FourOhFour/Magic_v2_8B](https://huggingface.co/FourOhFour/Magic_v2_8B) created using llama.cpp
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+
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+ # Original Model Card
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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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+
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+ axolotl version: `0.4.1`
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+ ```yaml
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+ base_model: Dans-DiscountModels/Mistral-NeMo-Minitron-8B-Base-ChatML
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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: false
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+ load_in_4bit: false
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+ strict: false
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+
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+ datasets:
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+ - path: PocketDoc/Dans-MemoryCore-CoreCurriculum-Small
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+ type: sharegpt
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+ conversation: chatml
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+ - path: NewEden/Kalo-Opus-Instruct-22k-Refusal-Murdered
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+ type: sharegpt
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+ conversation: chatml
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+ - path: Epiculous/Synthstruct-Gens-v1.1-Filtered-n-Cleaned
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+ type: sharegpt
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+ conversation: chatml
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+ - path: NewEden/Gryphe-Sonnet-3.5-35k-Subset
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+ type: sharegpt
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+ conversation: chatml
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+ - path: Nitral-AI/Reasoning-1shot_ShareGPT
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+ type: sharegpt
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+ conversation: chatml
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+ - path: Nitral-AI/GU_Instruct-ShareGPT
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+ type: sharegpt
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+ conversation: chatml
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+ - path: Nitral-AI/Medical_Instruct-ShareGPT
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+ type: sharegpt
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+ conversation: chatml
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+ - path: AquaV/Resistance-Sharegpt
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+ type: sharegpt
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+ conversation: chatml
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+ - path: AquaV/US-Army-Survival-Sharegpt
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+ type: sharegpt
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+ conversation: chatml
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+ - path: Gryphe/Sonnet3.5-SlimOrcaDedupCleaned
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+ type: sharegpt
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+ conversation: chatml
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+
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+ chat_template: chatml
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+
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+ val_set_size: 0.002
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+ output_dir: ./outputs/out
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+
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+ adapter:
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+ lora_r:
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+ lora_alpha:
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+ lora_dropout:
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+ lora_target_linear:
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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: false
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+ pad_to_sequence_len: true
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+
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+ plugins:
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+ - axolotl.integrations.liger.LigerPlugin
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+ liger_rope: true
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+ liger_rms_norm: true
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+ liger_swiglu: true
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+ liger_fused_linear_cross_entropy: true
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+
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+ wandb_project: mini8B
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+ wandb_entity:
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+ wandb_watch:
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+ wandb_name: mini8B
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+ wandb_log_model:
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+
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+ gradient_accumulation_steps: 4
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+ micro_batch_size: 2
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+ num_epochs: 2
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+ optimizer: adamw_bnb_8bit
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+ lr_scheduler: cosine
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+ learning_rate: 0.00001
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+ weight_decay: 0.05
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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: auto
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+ fp16:
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+ tf32: true
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+
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+ gradient_checkpointing: 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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+
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+ warmup_ratio: 0.1
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+ evals_per_epoch: 4
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+ eval_table_size:
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+ eval_max_new_tokens: 128
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+ saves_per_epoch: 2
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+
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+ debug:
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+ deepspeed: deepspeed_configs/zero3_bf16.json
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+ fsdp:
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+ fsdp_config:
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+
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+ special_tokens:
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+ pad_token: <pad>
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+
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+ ```
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+
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+ </details><br>
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+
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+ # outputs/out
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+
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+ This model is a fine-tuned version of [Dans-DiscountModels/Mistral-NeMo-Minitron-8B-Base-ChatML](https://huggingface.co/Dans-DiscountModels/Mistral-NeMo-Minitron-8B-Base-ChatML) on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 1.5341
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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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: 2
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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: 4
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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_steps: 91
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+ - num_epochs: 2
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss |
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+ |:-------------:|:------:|:----:|:---------------:|
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+ | 1.2548 | 0.0022 | 1 | 2.0884 |
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+ | 0.7712 | 0.2503 | 114 | 1.6165 |
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+ | 0.7566 | 0.5005 | 228 | 1.5734 |
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+ | 0.7241 | 0.7508 | 342 | 1.5579 |
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+ | 0.6994 | 1.0011 | 456 | 1.5401 |
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+ | 0.6186 | 1.2499 | 570 | 1.5433 |
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+ | 0.6102 | 1.5003 | 684 | 1.5366 |
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+ | 0.5926 | 1.7507 | 798 | 1.5341 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.45.0.dev0
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+ - Pytorch 2.4.0+cu121
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+ - Datasets 2.21.0
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+ - Tokenizers 0.19.1
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+