End of training

README.md

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+---
+license: apache-2.0
+library_name: peft
+tags:
+- generated_from_trainer
+base_model: mistralai/Mixtral-8x7B-v0.1
+model-index:
+- name: mixtral-8x7b-v0.1-english-to-hinglish-translation
+  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. -->
+
+# mixtral-8x7b-v0.1-english-to-hinglish-translation
+
+This model is a fine-tuned version of [mistralai/Mixtral-8x7B-v0.1](https://huggingface.co/mistralai/Mixtral-8x7B-v0.1) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 1.0769
+- Rouge Scores: {'rouge1': 90.45408202972536, 'rouge2': 79.5425441228359, 'rougeL': 83.99846297860634, 'rougeLsum': 90.43739034131012}
+- Bleu Scores: [0.0002881182166187815, 0.0002842750061873772, 0.0002764768847375588, 0.00026750640347869873]
+- Gen Len: 2048.0
+
+## 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: 0.0001
+- train_batch_size: 2
+- eval_batch_size: 8
+- seed: 42
+- gradient_accumulation_steps: 2
+- total_train_batch_size: 4
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: cosine
+- num_epochs: 2
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Rouge Scores                                                                                                            | Bleu Scores                                                                                   | Gen Len  |
+|:-------------:|:-----:|:----:|:---------------:|:-----------------------------------------------------------------------------------------------------------------------:|:---------------------------------------------------------------------------------------------:|:--------:|
+| 1.1771        | 1.0   | 500  | 1.0579          | {'rouge1': 90.70255400902434, 'rouge2': 79.76770190068221, 'rougeL': 84.00261479965636, 'rougeLsum': 90.69363147075731} | [0.00028395954091190866, 0.0002796973368739713, 0.0002722057765709132, 0.000263740024418467]  | 2047.996 |
+| 0.7788        | 2.0   | 1000 | 1.0769          | {'rouge1': 90.45408202972536, 'rouge2': 79.5425441228359, 'rougeL': 83.99846297860634, 'rougeLsum': 90.43739034131012}  | [0.0002881182166187815, 0.0002842750061873772, 0.0002764768847375588, 0.00026750640347869873] | 2048.0   |
+
+
+### Framework versions
+
+- PEFT 0.8.2
+- Transformers 4.38.0.dev0
+- Pytorch 2.1.0+cu118
+- Datasets 2.16.2.dev0
+- Tokenizers 0.15.1

adapter_config.json

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+{
+  "alpha_pattern": {},
+  "auto_mapping": null,
+  "base_model_name_or_path": "mistralai/Mixtral-8x7B-v0.1",
+  "bias": "none",
+  "fan_in_fan_out": false,
+  "inference_mode": true,
+  "init_lora_weights": true,
+  "layers_pattern": null,
+  "layers_to_transform": null,
+  "loftq_config": {},
+  "lora_alpha": 64,
+  "lora_dropout": 0.0,
+  "megatron_config": null,
+  "megatron_core": "megatron.core",
+  "modules_to_save": null,
+  "peft_type": "LORA",
+  "r": 64,
+  "rank_pattern": {},
+  "revision": null,
+  "target_modules": [
+    "w3",
+    "q_proj",
+    "w2",
+    "o_proj",
+    "w1",
+    "v_proj",
+    "k_proj"
+  ],
+  "task_type": "CAUSAL_LM",
+  "use_rslora": false
+}

adapter_model.safetensors

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+size 3842250744

training_args.bin

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