End of training

README.md

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+---
+library_name: transformers
+license: apache-2.0
+base_model: google-bert/bert-base-multilingual-cased
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- precision
+- recall
+- f1
+model-index:
+- name: bert-f1-durga-muhammad-c
+  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-f1-durga-muhammad-c
+
+This model is a fine-tuned version of [google-bert/bert-base-multilingual-cased](https://huggingface.co/google-bert/bert-base-multilingual-cased) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0001
+- Accuracy: 1.0
+- Precision: 1.0
+- Recall: 1.0
+- F1: 1.0
+
+## 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: 24
+- eval_batch_size: 24
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 1000
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1    |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:-----:|
+| 0.0245        | 1.0   | 42   | 0.0241          | 0.995    | 0.995     | 0.995  | 0.995 |
+| 0.0032        | 2.0   | 84   | 0.0081          | 0.999    | 0.999     | 0.999  | 0.999 |
+| 0.0011        | 3.0   | 126  | 0.0075          | 0.999    | 0.999     | 0.999  | 0.999 |
+| 0.0008        | 4.0   | 168  | 0.0068          | 0.999    | 0.999     | 0.999  | 0.999 |
+| 0.0006        | 5.0   | 210  | 0.0078          | 0.999    | 0.999     | 0.999  | 0.999 |
+| 0.0012        | 6.0   | 252  | 0.0063          | 0.999    | 0.999     | 0.999  | 0.999 |
+| 0.0022        | 7.0   | 294  | 0.0015          | 1.0      | 1.0       | 1.0    | 1.0   |
+| 0.0004        | 8.0   | 336  | 0.0031          | 0.999    | 0.999     | 0.999  | 0.999 |
+| 0.0003        | 9.0   | 378  | 0.0002          | 1.0      | 1.0       | 1.0    | 1.0   |
+| 0.0002        | 10.0  | 420  | 0.0002          | 1.0      | 1.0       | 1.0    | 1.0   |
+| 0.0002        | 11.0  | 462  | 0.0001          | 1.0      | 1.0       | 1.0    | 1.0   |
+| 0.0002        | 12.0  | 504  | 0.0001          | 1.0      | 1.0       | 1.0    | 1.0   |
+| 0.0002        | 13.0  | 546  | 0.0001          | 1.0      | 1.0       | 1.0    | 1.0   |
+| 0.0001        | 14.0  | 588  | 0.0001          | 1.0      | 1.0       | 1.0    | 1.0   |
+| 0.0001        | 15.0  | 630  | 0.0001          | 1.0      | 1.0       | 1.0    | 1.0   |
+| 0.0001        | 16.0  | 672  | 0.0001          | 1.0      | 1.0       | 1.0    | 1.0   |
+| 0.0001        | 17.0  | 714  | 0.0001          | 1.0      | 1.0       | 1.0    | 1.0   |
+
+
+### Framework versions
+
+- Transformers 4.44.2
+- Pytorch 2.5.0+cu121
+- Datasets 3.1.0
+- Tokenizers 0.19.1

config.json

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+{
+  "_name_or_path": "google-bert/bert-base-multilingual-cased",
+  "architectures": [
+    "BertForSequenceClassification"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "classifier_dropout": null,
+  "directionality": "bidi",
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 768,
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "layer_norm_eps": 1e-12,
+  "max_position_embeddings": 512,
+  "model_type": "bert",
+  "num_attention_heads": 12,
+  "num_hidden_layers": 12,
+  "pad_token_id": 0,
+  "pooler_fc_size": 768,
+  "pooler_num_attention_heads": 12,
+  "pooler_num_fc_layers": 3,
+  "pooler_size_per_head": 128,
+  "pooler_type": "first_token_transform",
+  "position_embedding_type": "absolute",
+  "problem_type": "single_label_classification",
+  "torch_dtype": "float32",
+  "transformers_version": "4.44.2",
+  "type_vocab_size": 2,
+  "use_cache": true,
+  "vocab_size": 119547
+}

model.safetensors

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training_args.bin

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