Model save

README.md

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+---
+base_model: meta-llama/Meta-Llama-3-8B-Instruct
+library_name: peft
+license: llama3
+tags:
+- trl
+- sft
+- generated_from_trainer
+model-index:
+- name: Meta-Llama-3-8B-Instruct-mirage-meta-llama-3-sft-instruct
+  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. -->
+
+# Meta-Llama-3-8B-Instruct-mirage-meta-llama-3-sft-instruct
+
+This model is a fine-tuned version of [meta-llama/Meta-Llama-3-8B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3-8B-Instruct) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.2432
+
+## 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: 0.0002
+- train_batch_size: 2
+- eval_batch_size: 2
+- seed: 42
+- distributed_type: multi-GPU
+- num_devices: 4
+- gradient_accumulation_steps: 2
+- total_train_batch_size: 16
+- total_eval_batch_size: 8
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: cosine
+- lr_scheduler_warmup_ratio: 0.1
+- num_epochs: 1
+
+### Training results
+
+| Training Loss | Epoch  | Step | Validation Loss |
+|:-------------:|:------:|:----:|:---------------:|
+| 0.3403        | 0.0597 | 200  | 0.3074          |
+| 0.3224        | 0.1195 | 400  | 0.2954          |
+| 0.3055        | 0.1792 | 600  | 0.2886          |
+| 0.2899        | 0.2389 | 800  | 0.2804          |
+| 0.3116        | 0.2987 | 1000 | 0.2772          |
+| 0.3101        | 0.3584 | 1200 | 0.2728          |
+| 0.2913        | 0.4182 | 1400 | 0.2679          |
+| 0.2765        | 0.4779 | 1600 | 0.2625          |
+| 0.2697        | 0.5376 | 1800 | 0.2601          |
+| 0.2759        | 0.5974 | 2000 | 0.2557          |
+| 0.264         | 0.6571 | 2200 | 0.2524          |
+| 0.2705        | 0.7168 | 2400 | 0.2490          |
+| 0.2694        | 0.7766 | 2600 | 0.2466          |
+| 0.2639        | 0.8363 | 2800 | 0.2450          |
+| 0.2598        | 0.8961 | 3000 | 0.2435          |
+| 0.2483        | 0.9558 | 3200 | 0.2432          |
+
+
+### Framework versions
+
+- PEFT 0.10.0
+- Transformers 4.44.0
+- Pytorch 2.4.0+cu121
+- Datasets 2.20.0
+- Tokenizers 0.19.1

all_results.json

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+{
+    "epoch": 1.0,
+    "total_flos": 1.6414748941746176e+16,
+    "train_loss": 0.27713136451503567,
+    "train_runtime": 31532.8493,
+    "train_samples": 53566,
+    "train_samples_per_second": 1.699,
+    "train_steps_per_second": 0.106
+}

train_results.json

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+{
+    "epoch": 1.0,
+    "total_flos": 1.6414748941746176e+16,
+    "train_loss": 0.27713136451503567,
+    "train_runtime": 31532.8493,
+    "train_samples": 53566,
+    "train_samples_per_second": 1.699,
+    "train_steps_per_second": 0.106
+}