Model save

README.md

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+---
+base_model: Hartunka/tiny_bert_rand_100_v1
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- f1
+model-index:
+- name: tiny_bert_rand_100_v1_mrpc
+  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. -->
+
+# tiny_bert_rand_100_v1_mrpc
+
+This model is a fine-tuned version of [Hartunka/tiny_bert_rand_100_v1](https://huggingface.co/Hartunka/tiny_bert_rand_100_v1) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.9900
+- Accuracy: 0.6446
+- F1: 0.7330
+- Combined Score: 0.6888
+
+## 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: 5e-05
+- train_batch_size: 256
+- eval_batch_size: 256
+- seed: 10
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 50
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Combined Score |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------------:|
+| 0.6273        | 1.0   | 15   | 0.6087          | 0.6887   | 0.8025 | 0.7456         |
+| 0.5923        | 2.0   | 30   | 0.5959          | 0.6985   | 0.8051 | 0.7518         |
+| 0.5507        | 3.0   | 45   | 0.6265          | 0.7059   | 0.8107 | 0.7583         |
+| 0.5072        | 4.0   | 60   | 0.6902          | 0.6152   | 0.6879 | 0.6515         |
+| 0.4237        | 5.0   | 75   | 0.7022          | 0.6667   | 0.7527 | 0.7097         |
+| 0.3165        | 6.0   | 90   | 0.8693          | 0.6446   | 0.7290 | 0.6868         |
+| 0.2385        | 7.0   | 105  | 0.9900          | 0.6446   | 0.7330 | 0.6888         |
+
+
+### Framework versions
+
+- Transformers 4.40.0
+- Pytorch 2.6.0+cu124
+- Datasets 3.5.0
+- Tokenizers 0.19.1

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