End of training

README.md

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+---
+library_name: peft
+tags:
+- generated_from_trainer
+base_model: NousResearch/Llama-2-7b-hf
+model-index:
+- name: llama2-7b-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. -->
+
+# llama2-7b-english-to-hinglish-translation
+
+This model is a fine-tuned version of [NousResearch/Llama-2-7b-hf](https://huggingface.co/NousResearch/Llama-2-7b-hf) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.7718
+- Rouge Scores: {'rouge1': 91.95734764873546, 'rouge2': 82.32931400113223, 'rougeL': 85.99741932162073, 'rougeLsum': 91.94841950416424}
+- Bleu Scores: [0.9416174113277822, 0.927443422067012, 0.9093890905268396, 0.8902085653786349]
+- 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 |
+|:-------------:|:-----:|:----:|:---------------:|:-----------------------------------------------------------------------------------------------------------------------:|:--------------------------------------------------------------------------------:|:-------:|
+| 0.8676        | 1.0   | 500  | 0.7965          | {'rouge1': 91.95351666069791, 'rouge2': 82.14665839576412, 'rougeL': 85.51462558903678, 'rougeLsum': 91.94448847318316} | [0.9428007493469047, 0.9283594260300487, 0.9099607650770003, 0.8903936529899328] | 2048.0  |
+| 0.6641        | 2.0   | 1000 | 0.7718          | {'rouge1': 91.95734764873546, 'rouge2': 82.32931400113223, 'rougeL': 85.99741932162073, 'rougeLsum': 91.94841950416424} | [0.9416174113277822, 0.927443422067012, 0.9093890905268396, 0.8902085653786349]  | 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": null,
+  "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",
+    "w2",
+    "q_proj",
+    "v_proj",
+    "w1",
+    "o_proj",
+    "k_proj"
+  ],
+  "task_type": "CAUSAL_LM",
+  "use_rslora": false
+}

adapter_model.safetensors

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+size 268474624

training_args.bin

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