End of training

README.md

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+---
+library_name: transformers
+license: apache-2.0
+base_model: distilbert-base-uncased
+tags:
+- generated_from_trainer
+model-index:
+- name: IMDb_data_subset-MLM_with-custom_collator-distilbert-base-uncased
+  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. -->
+
+# IMDb_data_subset-MLM_with-custom_collator-distilbert-base-uncased
+
+This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 3.2538
+- Model Preparation Time: 0.0042
+
+## 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: 64
+- eval_batch_size: 64
+- seed: 42
+- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
+- lr_scheduler_type: linear
+- num_epochs: 5
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Model Preparation Time |
+|:-------------:|:-----:|:----:|:---------------:|:----------------------:|
+| 3.5579        | 1.0   | 157  | 3.3058          | 0.0042                 |
+| 3.3945        | 2.0   | 314  | 3.2732          | 0.0042                 |
+| 3.3487        | 3.0   | 471  | 3.2542          | 0.0042                 |
+| 3.3088        | 4.0   | 628  | 3.2237          | 0.0042                 |
+| 3.2961        | 5.0   | 785  | 3.2538          | 0.0042                 |
+
+
+### Framework versions
+
+- Transformers 4.50.0
+- Pytorch 2.6.0+cu124
+- Datasets 3.4.1
+- Tokenizers 0.21.1

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