Model save

README.md

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+---
+license: apache-2.0
+library_name: peft
+tags:
+- trl
+- sft
+- generated_from_trainer
+base_model: mistralai/Mistral-7B-Instruct-v0.2
+datasets:
+- generator
+metrics:
+- bleu
+- rouge
+model-index:
+- name: Mistral-7B-Instruct-v0.2-advisegpt-v0.6
+  results: []
+---
+
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
+
+# Mistral-7B-Instruct-v0.2-advisegpt-v0.6
+
+This model is a fine-tuned version of [mistralai/Mistral-7B-Instruct-v0.2](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.2) on the generator dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0767
+- Bleu: {'bleu': 0.9584832765902116, 'precisions': [0.9778312591422885, 0.9625878953932084, 0.9518774970032065, 0.9430684559898991], 'brevity_penalty': 0.9997177244264667, 'length_ratio': 0.9997177642587203, 'translation_length': 1289338, 'reference_length': 1289702}
+- Rouge: {'rouge1': 0.9761023152523122, 'rouge2': 0.9590922549283836, 'rougeL': 0.9747297976860183, 'rougeLsum': 0.9758442544146716}
+- Exact Match: {'exact_match': 0.0}
+
+## Model description
+
+More information needed
+
+## Intended uses & limitations
+
+More information needed
+
+## Training and evaluation data
+
+More information needed
+
+## Training procedure
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- learning_rate: 2e-05
+- train_batch_size: 3
+- eval_batch_size: 1
+- seed: 42
+- gradient_accumulation_steps: 10
+- total_train_batch_size: 30
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: cosine
+- num_epochs: 3
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch  | Step | Validation Loss | Bleu                                                                                                                                                                                                                                                                | Rouge                                                                                                                       | Exact Match          |
+|:-------------:|:------:|:----:|:---------------:|:-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------:|:---------------------------------------------------------------------------------------------------------------------------:|:--------------------:|
+| 0.067         | 0.9998 | 809  | 0.0945          | {'bleu': 0.9492918853166353, 'precisions': [0.9733554685833311, 0.9543042005762523, 0.9412361771045687, 0.9307382413966919], 'brevity_penalty': 0.9994904502180469, 'length_ratio': 0.9994905799944483, 'translation_length': 1289045, 'reference_length': 1289702} | {'rouge1': 0.9712558044405124, 'rouge2': 0.9500703853191179, 'rougeL': 0.9690578078497468, 'rougeLsum': 0.9708044674114953} | {'exact_match': 0.0} |
+| 0.0527        | 1.9995 | 1618 | 0.0779          | {'bleu': 0.9568445996007577, 'precisions': [0.977026202258449, 0.961055539100332, 0.9498195483213825, 0.9405540074014527], 'brevity_penalty': 0.9998193217903225, 'length_ratio': 0.9998193381106644, 'translation_length': 1289469, 'reference_length': 1289702}   | {'rouge1': 0.9753094821779227, 'rouge2': 0.9574822736836266, 'rougeL': 0.9737984768450723, 'rougeLsum': 0.9750220632065946} | {'exact_match': 0.0} |
+| 0.0471        | 2.9993 | 2427 | 0.0767          | {'bleu': 0.9584832765902116, 'precisions': [0.9778312591422885, 0.9625878953932084, 0.9518774970032065, 0.9430684559898991], 'brevity_penalty': 0.9997177244264667, 'length_ratio': 0.9997177642587203, 'translation_length': 1289338, 'reference_length': 1289702} | {'rouge1': 0.9761023152523122, 'rouge2': 0.9590922549283836, 'rougeL': 0.9747297976860183, 'rougeLsum': 0.9758442544146716} | {'exact_match': 0.0} |
+
+
+### Framework versions
+
+- PEFT 0.10.0
+- Transformers 4.40.2
+- Pytorch 2.3.0+cu121
+- Datasets 2.19.1
+- Tokenizers 0.19.1