End of training

README.md

@@ -1,77 +1,67 @@
----
-license: apache-2.0
-base_model: google-bert/bert-base-cased
-tags:
-- generated_from_trainer
-metrics:
-- accuracy
-model-index:
-- name: BERT-base
-  results: []
-datasets:
-- Davlan/sib200
-language:
-- lt
-- en
-pipeline_tag: text-classification
----
-
-<!-- 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. -->
-
-# BERT-base
-
-This model is a fine-tuned version of [google-bert/bert-base-cased](https://huggingface.co/google-bert/bert-base-cased) on an unknown dataset.
-It achieves the following results on the evaluation set:
-- Loss: 1.4498
-- Accuracy: 0.4657
-
-## 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: 32
-- eval_batch_size: 32
-- seed: 42
-- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
-- lr_scheduler_type: linear
-- num_epochs: 12
-
-### Training results
-
-| Training Loss | Epoch | Step | Validation Loss | Accuracy |
-|:-------------:|:-----:|:----:|:---------------:|:--------:|
-| No log        | 1.0   | 22   | 1.8823          | 0.25     |
-| No log        | 2.0   | 44   | 1.7918          | 0.2892   |
-| No log        | 3.0   | 66   | 1.7041          | 0.3578   |
-| No log        | 4.0   | 88   | 1.6625          | 0.3480   |
-| No log        | 5.0   | 110  | 1.6353          | 0.3971   |
-| No log        | 6.0   | 132  | 1.5817          | 0.4118   |
-| No log        | 7.0   | 154  | 1.5344          | 0.4069   |
-| No log        | 8.0   | 176  | 1.5128          | 0.4804   |
-| No log        | 9.0   | 198  | 1.4906          | 0.4559   |
-| No log        | 10.0  | 220  | 1.4587          | 0.4755   |
-| No log        | 11.0  | 242  | 1.4590          | 0.4951   |
-| No log        | 12.0  | 264  | 1.4498          | 0.4657   |
-
-
-### Framework versions
-
-- Transformers 4.44.0
-- Pytorch 2.4.0+cu124
-- Datasets 2.20.0
-- Tokenizers 0.19.1
+---
+license: apache-2.0
+base_model: google-bert/bert-base-cased
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+model-index:
+- name: BERT-base
+  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. -->
+
+# BERT-base
+
+This model is a fine-tuned version of [google-bert/bert-base-cased](https://huggingface.co/google-bert/bert-base-cased) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 1.6524
+- Accuracy: 0.4265
+
+## 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: 32
+- eval_batch_size: 32
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 8
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| No log        | 1.0   | 22   | 1.8763          | 0.2549   |
+| No log        | 2.0   | 44   | 1.8652          | 0.25     |
+| No log        | 3.0   | 66   | 1.7901          | 0.3088   |
+| No log        | 4.0   | 88   | 1.7617          | 0.3235   |
+| No log        | 5.0   | 110  | 1.7064          | 0.3676   |
+| No log        | 6.0   | 132  | 1.6792          | 0.4167   |
+| No log        | 7.0   | 154  | 1.6574          | 0.4216   |
+| No log        | 8.0   | 176  | 1.6524          | 0.4265   |
+
+
+### Framework versions
+
+- Transformers 4.44.0
+- Pytorch 2.4.0+cpu
+- Datasets 2.21.0
+- Tokenizers 0.19.1

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