Model save

README.md

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+---
+license: apache-2.0
+base_model: mistralai/Mistral-7B-v0.1
+tags:
+- generated_from_trainer
+model-index:
+- name: zephyr-7b-sft-lora
+  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. -->
+
+# zephyr-7b-sft-lora
+
+This model is a fine-tuned version of [mistralai/Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.7875
+
+## 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: 1
+- eval_batch_size: 1
+- seed: 42
+- distributed_type: multi-GPU
+- num_devices: 2
+- gradient_accumulation_steps: 128
+- total_train_batch_size: 256
+- total_eval_batch_size: 2
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: cosine
+- num_epochs: 1
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss |
+|:-------------:|:-----:|:----:|:---------------:|
+| 0.3188        | 1.0   | 1    | 0.7875          |
+
+
+### Framework versions
+
+- Transformers 4.35.0
+- Pytorch 2.1.0
+- 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": "mistralai/Mistral-7B-v0.1",
+  "bias": "none",
+  "fan_in_fan_out": false,
+  "inference_mode": true,
+  "init_lora_weights": true,
+  "layers_pattern": null,
+  "layers_to_transform": null,
+  "lora_alpha": 16,
+  "lora_dropout": 0.1,
+  "modules_to_save": null,
+  "peft_type": "LORA",
+  "r": 64,
+  "rank_pattern": {},
+  "revision": null,
+  "target_modules": [
+    "q_proj",
+    "k_proj",
+    "v_proj",
+    "o_proj"
+  ],
+  "task_type": "CAUSAL_LM"
+}

adapter_model.safetensors

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all_results.json

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+{
+    "epoch": 1.0,
+    "eval_loss": 0.7874919176101685,
+    "eval_runtime": 123.3998,
+    "eval_samples": 101,
+    "eval_samples_per_second": 0.818,
+    "eval_steps_per_second": 0.413,
+    "train_loss": 0.31876903772354126,
+    "train_runtime": 358.693,
+    "train_samples": 101,
+    "train_samples_per_second": 0.282,
+    "train_steps_per_second": 0.003
+}

eval_results.json

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+{
+    "epoch": 1.0,
+    "eval_loss": 0.7874919176101685,
+    "eval_runtime": 123.3998,
+    "eval_samples": 101,
+    "eval_samples_per_second": 0.818,
+    "eval_steps_per_second": 0.413
+}

runs/Dec21_20-42-47_rPower2/events.out.tfevents.1703158993.rPower2.4096011.0

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runs/Dec28_20-31-59_rPower2/events.out.tfevents.1703763205.rPower2.1911033.0

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runs/Dec28_20-41-34_rPower2/events.out.tfevents.1703763715.rPower2.1917879.0

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runs/Dec28_20-48-24_rPower2/events.out.tfevents.1703764125.rPower2.1922741.0

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special_tokens_map.json

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+{
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+}

tokenizer_config.json

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+  "chat_template": "{% for message in messages %}\n{% if message['role'] == 'user' %}\n{{ '<|user|>\n' + message['content'] + eos_token }}\n{% elif message['role'] == 'system' %}\n{{ '<|system|>\n' + message['content'] + eos_token }}\n{% elif message['role'] == 'assistant' %}\n{{ '<|assistant|>\n'  + message['content'] + eos_token }}\n{% endif %}\n{% if loop.last and add_generation_prompt %}\n{{ '<|assistant|>' }}\n{% endif %}\n{% endfor %}",
+  "clean_up_tokenization_spaces": false,
+  "eos_token": "</s>",
+  "legacy": true,
+  "model_max_length": 2048,
+  "pad_token": "</s>",
+  "sp_model_kwargs": {},
+  "spaces_between_special_tokens": false,
+  "tokenizer_class": "LlamaTokenizer",
+  "unk_token": "<unk>",
+  "use_default_system_prompt": false
+}

train_results.json

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+    "train_runtime": 358.693,
+    "train_samples": 101,
+    "train_samples_per_second": 0.282,
+    "train_steps_per_second": 0.003
+}

trainer_state.json

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+}

training_args.bin

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