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- ---
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- license: apache-2.0
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- ---
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ ---
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+ license: other
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+ library_name: peft
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+ tags:
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+ - axolotl
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+ - generated_from_trainer
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+ base_model: deepseek-ai/deepseek-coder-1.3b-instruct
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+ model-index:
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+ - name: deepseek-code-1.3b-inst-NLQ2Cypher
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+ results: []
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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/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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+
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+ axolotl version: `0.4.0`
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+ ```yaml
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+ base_model: deepseek-ai/deepseek-coder-1.3b-instruct
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+ # base_model: Qwen/CodeQwen1.5-7B-Chat
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+ model_type: AutoModelForCausalLM
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+ tokenizer_type: AutoTokenizer
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+ is_mistral_derived_model: false
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+
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+ load_in_8bit: false
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+ load_in_4bit: true
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+ strict: false
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+
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+ lora_fan_in_fan_out: false
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+ data_seed: 49
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+ seed: 49
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+
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+ datasets:
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+ - path: sample_data/alpaca_synth_cypher.jsonl
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+ type: sharegpt
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+ conversation: alpaca
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+ dataset_prepared_path: last_run_prepared
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+ val_set_size: 0.1
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+ output_dir: ./qlora-alpaca-deepseek-1.3b-inst
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+ # output_dir: ./qlora-alpaca-out
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+
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+ # hub_model_id: jermyn/CodeQwen1.5-7B-Chat-NLQ2Cypher
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+ hub_model_id: jermyn/deepseek-code-1.3b-inst-NLQ2Cypher
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+
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+ adapter: qlora
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+ lora_model_dir:
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+
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+ sequence_len: 896
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+ sample_packing: false
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+ pad_to_sequence_len: true
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+
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+ lora_r: 32
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+ lora_alpha: 16
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+ lora_dropout: 0.05
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+ lora_target_linear: true
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+ lora_fan_in_fan_out:
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+ lora_target_modules:
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+ - gate_proj
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+ - down_proj
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+ - up_proj
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+ - q_proj
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+ - v_proj
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+ - k_proj
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+ - o_proj
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+
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+ # If you added new tokens to the tokenizer, you may need to save some LoRA modules because they need to know the new tokens.
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+ # For LLaMA and Mistral, you need to save `embed_tokens` and `lm_head`. It may vary for other models.
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+ # `embed_tokens` converts tokens to embeddings, and `lm_head` converts embeddings to token probabilities.
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+ # https://github.com/huggingface/peft/issues/334#issuecomment-1561727994
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+ # lora_modules_to_save:
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+ # - embed_tokens
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+ # - lm_head
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+
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+ wandb_project: fine-tune-axolotl
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+ wandb_entity: jermyn
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+
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+ gradient_accumulation_steps: 1
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+ micro_batch_size: 16
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+ eval_batch_size: 16
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+ num_epochs: 6
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+ optimizer: adamw_bnb_8bit
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+ lr_scheduler: cosine
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+ learning_rate: 0.0005
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+ max_grad_norm: 1.0
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+ adam_beta2: 0.95
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+ adam_epsilon: 0.00001
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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: true
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+ fp16: false
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+ tf32: false
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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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+ loss_watchdog_threshold: 5.0
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+ loss_watchdog_patience: 3
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+
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+ warmup_steps: 10
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+ evals_per_epoch: 4
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+ eval_table_size:
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+ eval_table_max_new_tokens: 128
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+ # saves_per_epoch: 6
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+ save_steps: 10
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+ save_total_limit: 3
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+ debug:
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+ weight_decay: 0.0
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+ fsdp:
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+ fsdp_config:
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+ # special_tokens:
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+ # bos_token: "<s>"
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+ # eos_token: "</s>"
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+ # unk_token: "<unk>"
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+ save_safetensors: true
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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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+ # deepseek-code-1.3b-inst-NLQ2Cypher
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+
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+ This model is a fine-tuned version of [deepseek-ai/deepseek-coder-1.3b-instruct](https://huggingface.co/deepseek-ai/deepseek-coder-1.3b-instruct) on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.3714
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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: 0.0005
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+ - train_batch_size: 16
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+ - eval_batch_size: 16
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+ - seed: 49
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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: 6
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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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+ | 1.8723 | 0.1429 | 1 | 1.6354 |
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+ | 1.9222 | 0.2857 | 2 | 1.6236 |
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+ | 1.7038 | 0.5714 | 4 | 1.4355 |
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+ | 1.2833 | 0.8571 | 6 | 0.9288 |
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+ | 0.6389 | 1.1429 | 8 | 0.7050 |
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+ | 0.401 | 1.4286 | 10 | 0.5980 |
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+ | 0.2982 | 1.7143 | 12 | 0.5694 |
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+ | 0.3225 | 2.0 | 14 | 0.5651 |
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+ | 0.2214 | 2.2857 | 16 | 0.5221 |
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+ | 0.1375 | 2.5714 | 18 | 0.4537 |
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+ | 0.1058 | 2.8571 | 20 | 0.3971 |
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+ | 0.0945 | 3.1429 | 22 | 0.3698 |
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+ | 0.1352 | 3.4286 | 24 | 0.3518 |
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+ | 0.0688 | 3.7143 | 26 | 0.3420 |
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+ | 0.0677 | 4.0 | 28 | 0.3508 |
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+ | 0.0506 | 4.2857 | 30 | 0.3577 |
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+ | 0.1056 | 4.5714 | 32 | 0.3714 |
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+ | 0.0839 | 4.8571 | 34 | 0.3710 |
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+ | 0.0562 | 5.1429 | 36 | 0.3717 |
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+ | 0.0715 | 5.4286 | 38 | 0.3749 |
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+ | 0.0708 | 5.7143 | 40 | 0.3709 |
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+ | 0.07 | 6.0 | 42 | 0.3714 |
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+
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+
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+ ### Framework versions
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+
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+ - PEFT 0.10.0
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+ - Transformers 4.40.2
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+ - Pytorch 2.1.2+cu118
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+ - Datasets 2.19.1
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+ - Tokenizers 0.19.1