End of training

README.md

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+---
+base_model: meta-llama/Llama-2-13b-hf
+tags:
+- generated_from_trainer
+model-index:
+- name: radiopaedia_cl-llama2_13b-240311
+  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. -->
+
+# radiopaedia_cl-llama2_13b-240311
+
+This model is a fine-tuned version of [meta-llama/Llama-2-13b-hf](https://huggingface.co/meta-llama/Llama-2-13b-hf) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.7476
+
+## 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: 0.0003
+- train_batch_size: 8
+- eval_batch_size: 16
+- seed: 42
+- gradient_accumulation_steps: 2
+- total_train_batch_size: 16
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_steps: 10
+- num_epochs: 2
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss |
+|:-------------:|:-----:|:----:|:---------------:|
+| 0.8773        | 0.05  | 20   | 0.8701          |
+| 0.8515        | 0.11  | 40   | 0.8439          |
+| 0.8288        | 0.16  | 60   | 0.8311          |
+| 0.8047        | 0.21  | 80   | 0.8179          |
+| 0.7462        | 0.27  | 100  | 0.8031          |
+| 0.852         | 0.32  | 120  | 0.7854          |
+| 0.8301        | 0.37  | 140  | 0.7937          |
+| 0.8407        | 0.42  | 160  | 0.7798          |
+| 0.7099        | 0.48  | 180  | 0.7690          |
+| 0.8138        | 0.53  | 200  | 0.7630          |
+| 0.8015        | 0.58  | 220  | 0.7670          |
+| 0.6831        | 0.64  | 240  | 0.7592          |
+| 0.7111        | 0.69  | 260  | 0.7601          |
+| 0.6946        | 0.74  | 280  | 0.7461          |
+| 0.6754        | 0.8   | 300  | 0.7514          |
+| 0.8267        | 0.85  | 320  | 0.7388          |
+| 0.7297        | 0.9   | 340  | 0.7372          |
+| 0.6722        | 0.96  | 360  | 0.7306          |
+| 0.5094        | 1.01  | 380  | 0.7278          |
+| 0.49          | 1.06  | 400  | 0.7530          |
+| 0.5015        | 1.12  | 420  | 0.7643          |
+| 0.4161        | 1.17  | 440  | 0.7585          |
+| 0.5348        | 1.22  | 460  | 0.7661          |
+| 0.4794        | 1.27  | 480  | 0.7525          |
+| 0.4915        | 1.33  | 500  | 0.7573          |
+| 0.4564        | 1.38  | 520  | 0.7667          |
+| 0.5295        | 1.43  | 540  | 0.7640          |
+| 0.503         | 1.49  | 560  | 0.7604          |
+| 0.3933        | 1.54  | 580  | 0.7602          |
+| 0.4384        | 1.59  | 600  | 0.7655          |
+| 0.406         | 1.65  | 620  | 0.7531          |
+| 0.5174        | 1.7   | 640  | 0.7473          |
+| 0.4811        | 1.75  | 660  | 0.7457          |
+| 0.4586        | 1.81  | 680  | 0.7519          |
+| 0.4957        | 1.86  | 700  | 0.7469          |
+| 0.4006        | 1.91  | 720  | 0.7458          |
+| 0.454         | 1.97  | 740  | 0.7476          |
+
+
+### Framework versions
+
+- Transformers 4.35.2
+- Pytorch 2.0.1+cu117
+- Datasets 2.14.6
+- Tokenizers 0.14.1

adapter_config.json

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+{
+  "alpha_pattern": {},
+  "auto_mapping": null,
+  "base_model_name_or_path": "meta-llama/Llama-2-13b-hf",
+  "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": 16,
+  "lora_dropout": 0.05,
+  "megatron_config": null,
+  "megatron_core": "megatron.core",
+  "modules_to_save": null,
+  "peft_type": "LORA",
+  "r": 2,
+  "rank_pattern": {},
+  "revision": null,
+  "target_modules": [
+    "v_proj",
+    "gate_proj",
+    "o_proj",
+    "q_proj",
+    "k_proj",
+    "up_proj",
+    "down_proj"
+  ],
+  "task_type": "CAUSAL_LM",
+  "use_rslora": false
+}

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training_args.bin

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