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Model: UaKidDev/distilgpt2-instruct
Source: Original Platform

README.md

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+---
+library_name: transformers
+license: apache-2.0
+base_model: distilgpt2
+tags:
+- generated_from_trainer
+model-index:
+- name: distilgpt2-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. -->
+
+# distilgpt2-instruct
+
+This model is a fine-tuned version of [distilgpt2](https://huggingface.co/distilgpt2) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 3.1097
+
+## 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: 3e-05
+- train_batch_size: 8
+- eval_batch_size: 16
+- seed: 42
+- gradient_accumulation_steps: 2
+- total_train_batch_size: 16
+- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
+- lr_scheduler_type: linear
+- num_epochs: 1
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch  | Step | Validation Loss |
+|:-------------:|:------:|:----:|:---------------:|
+| 3.6082        | 0.0757 | 200  | 3.4527          |
+| 3.4472        | 0.1514 | 400  | 3.3252          |
+| 3.3842        | 0.2271 | 600  | 3.2697          |
+| 3.3915        | 0.3027 | 800  | 3.2255          |
+| 3.3209        | 0.3784 | 1000 | 3.1980          |
+| 3.3036        | 0.4541 | 1200 | 3.1748          |
+| 3.2422        | 0.5298 | 1400 | 3.1566          |
+| 3.2840        | 0.6055 | 1600 | 3.1415          |
+| 3.2755        | 0.6812 | 1800 | 3.1303          |
+| 3.2236        | 0.7569 | 2000 | 3.1217          |
+| 3.1934        | 0.8325 | 2200 | 3.1143          |
+| 3.2567        | 0.9082 | 2400 | 3.1107          |
+| 3.2337        | 0.9839 | 2600 | 3.1097          |
+
+
+### Framework versions
+
+- Transformers 5.0.0
+- Pytorch 2.10.0+cu128
+- Datasets 4.8.5
+- Tokenizers 0.22.2