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-all-teacher-instruct-llama-3-sft
+  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-all-teacher-instruct-llama-3-sft
+
+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 the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.2593
+
+## 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 |
+|:-------------:|:------:|:----:|:---------------:|
+| 0.3535        | 0.0412 | 200  | 0.3586          |
+| 0.4117        | 0.0824 | 400  | 0.3371          |
+| 0.3577        | 0.1236 | 600  | 0.3277          |
+| 0.3594        | 0.1649 | 800  | 0.3194          |
+| 0.3603        | 0.2061 | 1000 | 0.3096          |
+| 0.3633        | 0.2473 | 1200 | 0.3063          |
+| 0.3078        | 0.2885 | 1400 | 0.3000          |
+| 0.3274        | 0.3297 | 1600 | 0.2948          |
+| 0.3474        | 0.3709 | 1800 | 0.2925          |
+| 0.3401        | 0.4122 | 2000 | 0.2875          |
+| 0.3124        | 0.4534 | 2200 | 0.2839          |
+| 0.3095        | 0.4946 | 2400 | 0.2802          |
+| 0.3532        | 0.5358 | 2600 | 0.2775          |
+| 0.301         | 0.5770 | 2800 | 0.2757          |
+| 0.3204        | 0.6182 | 3000 | 0.2712          |
+| 0.3158        | 0.6595 | 3200 | 0.2687          |
+| 0.3032        | 0.7007 | 3400 | 0.2667          |
+| 0.2851        | 0.7419 | 3600 | 0.2645          |
+| 0.2903        | 0.7831 | 3800 | 0.2629          |
+| 0.2943        | 0.8243 | 4000 | 0.2613          |
+| 0.2787        | 0.8655 | 4200 | 0.2603          |
+| 0.2558        | 0.9067 | 4400 | 0.2596          |
+| 0.3107        | 0.9480 | 4600 | 0.2593          |
+| 0.2894        | 0.9892 | 4800 | 0.2593          |
+
+
+### 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": 0.999896960329727,
+    "total_flos": 2.4144679757152256e+16,
+    "train_loss": 0.3040192322367887,
+    "train_runtime": 137718.1009,
+    "train_samples": 77636,
+    "train_samples_per_second": 0.564,
+    "train_steps_per_second": 0.035
+}

train_results.json

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+{
+    "epoch": 0.999896960329727,
+    "total_flos": 2.4144679757152256e+16,
+    "train_loss": 0.3040192322367887,
+    "train_runtime": 137718.1009,
+    "train_samples": 77636,
+    "train_samples_per_second": 0.564,
+    "train_steps_per_second": 0.035
+}