End of training

README.md

@@ -1,26 +1,68 @@
 ---
+library_name: transformers
+license: apache-2.0
+base_model: distilbert-base-uncased
 tags:
-- ml-intern
+- generated_from_trainer
+metrics:
+- accuracy
+- f1
+model-index:
+- name: patch-reward-model-v2
+  results: []
 ---
 
-# narcolepticchicken/patch-reward-model-v2
+<!-- 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. -->
 
-<!-- ml-intern-provenance -->
-## Generated by ML Intern
+# patch-reward-model-v2
 
-This model repository was generated by [ML Intern](https://github.com/huggingface/ml-intern), an agent for machine learning research and development on the Hugging Face Hub.
+This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.6882
+- Accuracy: 0.56
+- F1: 0.0
+- Auc: 0.5191
 
-- Try ML Intern: https://smolagents-ml-intern.hf.space
-- Source code: https://github.com/huggingface/ml-intern
+## Model description
 
-## Usage
+More information needed
 
-```python
-from transformers import AutoModelForCausalLM, AutoTokenizer
+## Intended uses & limitations
 
-model_id = 'narcolepticchicken/patch-reward-model-v2'
-tokenizer = AutoTokenizer.from_pretrained(model_id)
-model = AutoModelForCausalLM.from_pretrained(model_id)
-```
+More information needed
 
-For non-causal architectures, replace `AutoModelForCausalLM` with the appropriate `AutoModel` class.
+## 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: 16
+- eval_batch_size: 16
+- seed: 42
+- 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: 5
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1  | Auc    |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:---:|:------:|
+| 0.7096        | 1.0   | 25   | 0.6882          | 0.56     | 0.0 | 0.5191 |
+| 0.6851        | 2.0   | 50   | 0.6858          | 0.56     | 0.0 | 0.5199 |
+| 0.6961        | 3.0   | 75   | 0.6859          | 0.56     | 0.0 | 0.5463 |
+| 0.6915        | 4.0   | 100  | 0.6858          | 0.56     | 0.0 | 0.5548 |
+| 0.6936        | 5.0   | 125  | 0.6859          | 0.56     | 0.0 | 0.5548 |
+
+
+### Framework versions
+
+- Transformers 5.8.0
+- Pytorch 2.11.0+cu130
+- Datasets 4.8.5
+- Tokenizers 0.22.2

model.safetensors

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