Model save

README.md

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+---
+base_model: microsoft/Phi-3-mini-4k-instruct
+library_name: peft
+license: mit
+tags:
+- trl
+- sft
+- generated_from_trainer
+model-index:
+- name: hf_llama3_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. -->
+
+[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/hmosousa/huggingface/runs/d375v2e7)
+# hf_llama3_lora
+
+This model is a fine-tuned version of [microsoft/Phi-3-mini-4k-instruct](https://huggingface.co/microsoft/Phi-3-mini-4k-instruct) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 1.2972
+
+## 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: 4
+- eval_batch_size: 4
+- seed: 42
+- distributed_type: multi-GPU
+- num_devices: 5
+- gradient_accumulation_steps: 32
+- total_train_batch_size: 640
+- total_eval_batch_size: 20
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: cosine
+- lr_scheduler_warmup_steps: 1000
+- num_epochs: 10
+
+### Training results
+
+| Training Loss | Epoch  | Step | Validation Loss |
+|:-------------:|:------:|:----:|:---------------:|
+| 1.4042        | 0.1862 | 500  | 1.3990          |
+| 1.3445        | 0.3723 | 1000 | 1.3608          |
+| 1.291         | 0.5585 | 1500 | 1.3493          |
+| 1.264         | 0.7446 | 2000 | 1.3381          |
+| 1.2438        | 0.9308 | 2500 | 1.3257          |
+| 1.2333        | 1.1169 | 3000 | 1.3242          |
+| 1.2084        | 1.3031 | 3500 | 1.3167          |
+| 1.2227        | 1.4892 | 4000 | 1.3178          |
+| 1.2151        | 1.6754 | 4500 | 1.3092          |
+| 1.2114        | 1.8615 | 5000 | 1.3060          |
+| 1.1645        | 2.0477 | 5500 | 1.3068          |
+| 1.1793        | 2.2338 | 6000 | 1.3026          |
+| 1.1809        | 2.4200 | 6500 | 1.3014          |
+| 1.1934        | 2.6061 | 7000 | 1.2935          |
+| 1.175         | 2.7923 | 7500 | 1.2953          |
+| 1.1629        | 2.9784 | 8000 | 1.2954          |
+| 1.1559        | 3.1646 | 8500 | 1.2972          |
+
+
+### Framework versions
+
+- PEFT 0.9.0
+- Transformers 4.43.0.dev0
+- Pytorch 2.3.0+cu121
+- Datasets 2.18.0
+- Tokenizers 0.19.1

adapter_model.safetensors

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+oid sha256:30eabfceb6720d1a23c92d408c7b6f2f7fe368884da4f829d0f8590bcf3fef10
 size 402688552

all_results.json

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+{
+    "epoch": 3.1645937801770776,
+    "total_flos": 1.2178098370248075e+20,
+    "train_loss": 1.2383465781352099,
+    "train_runtime": 245543.4426,
+    "train_samples_per_second": 70.008,
+    "train_steps_per_second": 0.109
+}

train_results.json

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+{
+    "epoch": 3.1645937801770776,
+    "total_flos": 1.2178098370248075e+20,
+    "train_loss": 1.2383465781352099,
+    "train_runtime": 245543.4426,
+    "train_samples_per_second": 70.008,
+    "train_steps_per_second": 0.109
+}