Model save

README.md

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+---
+base_model: Hartunka/tiny_bert_km_100_v1
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+model-index:
+- name: tiny_bert_km_100_v1_mnli
+  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_km_100_v1_mnli
+
+This model is a fine-tuned version of [Hartunka/tiny_bert_km_100_v1](https://huggingface.co/Hartunka/tiny_bert_km_100_v1) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.9526
+- Accuracy: 0.6473
+
+## 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 |
+|:-------------:|:-----:|:-----:|:---------------:|:--------:|
+| 1.0013        | 1.0   | 1534  | 0.9411          | 0.5438   |
+| 0.9118        | 2.0   | 3068  | 0.8921          | 0.5829   |
+| 0.8579        | 3.0   | 4602  | 0.8575          | 0.6049   |
+| 0.811         | 4.0   | 6136  | 0.8428          | 0.6192   |
+| 0.7625        | 5.0   | 7670  | 0.8314          | 0.6324   |
+| 0.7165        | 6.0   | 9204  | 0.8438          | 0.6409   |
+| 0.6721        | 7.0   | 10738 | 0.8498          | 0.6440   |
+| 0.6294        | 8.0   | 12272 | 0.8689          | 0.6462   |
+| 0.5874        | 9.0   | 13806 | 0.9020          | 0.6466   |
+| 0.5462        | 10.0  | 15340 | 0.9526          | 0.6473   |
+
+
+### Framework versions
+
+- Transformers 4.40.0
+- Pytorch 2.6.0+cu124
+- Datasets 3.5.0
+- Tokenizers 0.19.1

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