End of training

README.md

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+---
+library_name: peft
+tags:
+- generated_from_trainer
+base_model: TheBloke/Llama-2-13B-fp16
+model-index:
+- name: llama-2-13b-fp16-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. -->
+
+# llama-2-13b-fp16-english-to-hinglish-translation
+
+This model is a fine-tuned version of [TheBloke/Llama-2-13B-fp16](https://huggingface.co/TheBloke/Llama-2-13B-fp16) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.7183
+- Rouge Scores: {'rouge1': 0.9211071676780294, 'rouge2': 0.8281733381382788, 'rougeL': 0.8654973199305598, 'rougeLsum': 0.921063419066345}
+- Bleu Scores: [0.9430761623222732, 0.9291834498365306, 0.9116309260224186, 0.8930302852359673]
+- 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 |
+|:-------------:|:-----:|:----:|:---------------:|:---------------------------------------------------------------------------------------------------------------------------:|:--------------------------------------------------------------------------------:|:-------:|
+| 0.7634        | 1.0   | 500  | 0.7242          | {'rouge1': 0.9226356216479343, 'rouge2': 0.8298878258164286, 'rougeL': 0.8653820285905314, 'rougeLsum': 0.9225028041599788} | [0.9438235001535462, 0.9299872780706577, 0.9124966958220146, 0.8939299935025186] | 2048.0  |
+| 0.5477        | 2.0   | 1000 | 0.7183          | {'rouge1': 0.9211071676780294, 'rouge2': 0.8281733381382788, 'rougeL': 0.8654973199305598, 'rougeLsum': 0.921063419066345}  | [0.9430761623222732, 0.9291834498365306, 0.9116309260224186, 0.8930302852359673] | 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": "TheBloke/Llama-2-13B-fp16",
+  "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": [
+    "up_proj",
+    "gate_proj",
+    "down_proj",
+    "o_proj",
+    "v_proj",
+    "q_proj",
+    "k_proj"
+  ],
+  "task_type": "CAUSAL_LM",
+  "use_rslora": false
+}

adapter_model.safetensors

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+size 1001465824

training_args.bin

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