--- license: mit base_model: DeepMount00/Mistral-Ita-7b tags: - axolotl - generated_from_trainer - psycology - companion model-index: - name: Samantha-ita-v0.1 results: [] datasets: - WasamiKirua/samantha-ita - WasamiKirua/psycology-dataset-ita language: - it --- [Built with Axolotl](https://github.com/OpenAccess-AI-Collective/axolotl)
See axolotl config axolotl version: `0.4.0` ```yaml base_model: DeepMount00/Mistral-Ita-7b model_type: MistralForCausalLM tokenizer_type: LlamaTokenizer load_in_8bit: false load_in_4bit: false strict: false datasets: - path: /workspace/datasets/samantha-ita-sharegpt.jsonl type: sharegpt field: conversations - path: /workspace/datasets/psycology-dataset-gpt-ita.jsonl type: sharegpt field: conversations chat_template: chatml hub_model_id: Samantha-ita-v0.1 dataset_prepared_path: val_set_size: 0.05 output_dir: ./out sequence_len: 8192 sample_packing: true pad_to_sequence_len: true eval_sample_packing: false wandb_project: samantha-mistral7b wandb_entity: wandb_watch: wandb_name: Samantha-ita-v0.1 wandb_log_model: gradient_accumulation_steps: 4 micro_batch_size: 2 num_epochs: 2 optimizer: adamw_bnb_8bit lr_scheduler: cosine learning_rate: 0.000006 # 0.000006 OK better curve # 0.0005 OK train_on_inputs: false group_by_length: false bf16: auto fp16: tf32: false gradient_checkpointing: true early_stopping_patience: resume_from_checkpoint: local_rank: logging_steps: 1 xformers_attention: flash_attention: true warmup_steps: 10 evals_per_epoch: 4 eval_table_size: eval_max_new_tokens: 128 saves_per_epoch: 1 debug: deepspeed: weight_decay: 0.0 fsdp: fsdp_config: special_tokens: bos_token: "" eos_token: "<|im_end|>" unk_token: "" tokens: - "<|im_start|>" - "<|im_end|>" ```

# Samantha-ita-v0.1 cover This model is a fine-tuned version of [DeepMount00/Mistral-Ita-7b](https://huggingface.co/DeepMount00/Mistral-Ita-7b) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.7069 ## Model description Samantha is a fine-tuned Italian version based on Eric Hartford's Samantha. For this, I utilized the pre-trained Mistral 7B version. The model performs excellently! Please take a look at the datasets used. ## Intended uses & limitations Sure, here's the corrected and improved version: Samantha is a proficient companion who understands and speaks Italian fluently. She has undergone training on various topics. In addition to the original Samantha dataset translated with GPT-4, I have also incorporated a psychology conversations dataset to further enrich Samantha's knowledge in the field of psychology." ## Chat Template ``` <|im_start|>system YOUR PROMPT<|im_end|> <|im_start|>user {prompt}<|im_end|> <|im_start|>assistant ``` ## Quantized Versions: GGUF availabile here: https://huggingface.co/WasamiKirua/Samantha-ita-mistral-v0.1-GGUF ## DPO Version DPO trained version available here: https://huggingface.co/WasamiKirua/Samantha-ita-mistral-v0.1-DPO ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 6e-06 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 10 - num_epochs: 2 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:-----:|:----:|:---------------:| | 1.9261 | 0.01 | 1 | 1.8998 | | 0.8902 | 0.25 | 28 | 0.8267 | | 0.8422 | 0.5 | 56 | 0.7604 | | 0.8338 | 0.75 | 84 | 0.7299 | | 0.8397 | 1.0 | 112 | 0.7136 | | 0.6859 | 1.22 | 140 | 0.7131 | | 0.6707 | 1.47 | 168 | 0.7082 | | 0.7041 | 1.72 | 196 | 0.7069 | | 0.6936 | 1.97 | 224 | 0.7069 | ### Framework versions - Transformers 4.40.0.dev0 - Pytorch 2.2.0 - Datasets 2.15.0 - Tokenizers 0.15.0