Duplicate from theophilusowiti/AfrimBert-QA

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README.md

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+---
+library_name: transformers
+base_model: amidblue/mBertKE
+tags:
+- generated_from_trainer
+metrics:
+- f1
+model-index:
+- name: AfrimBert-QA
+  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. -->
+
+# AfrimBert-QA
+
+This model is a fine-tuned version of [amidblue/mBertKE](https://huggingface.co/amidblue/mBertKE) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 1.4343
+- Model Preparation Time: 0.0029
+- Start Accuracy: 0.6830
+- End Accuracy: 0.6846
+- F1: 0.4070
+
+## 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: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
+- lr_scheduler_type: linear
+- num_epochs: 4
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Model Preparation Time | Start Accuracy | End Accuracy | F1     |
+|:-------------:|:-----:|:----:|:---------------:|:----------------------:|:--------------:|:------------:|:------:|
+| 1.3282        | 1.0   | 843  | 1.4711          | 0.0029                 | 0.6496         | 0.6483       | 0.3583 |
+| 1.2456        | 2.0   | 1686 | 1.3864          | 0.0029                 | 0.6750         | 0.6737       | 0.3833 |
+| 0.8872        | 3.0   | 2529 | 1.4020          | 0.0029                 | 0.6780         | 0.6833       | 0.3947 |
+| 0.7419        | 4.0   | 3372 | 1.4343          | 0.0029                 | 0.6830         | 0.6846       | 0.4070 |
+
+
+### Framework versions
+
+- Transformers 5.0.0
+- Pytorch 2.11.0+cu128
+- Datasets 4.0.0
+- Tokenizers 0.22.2

config.json

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+{
+  "add_cross_attention": false,
+  "architectures": [
+    "BertForQuestionAnswering"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "bos_token_id": null,
+  "classifier_dropout": null,
+  "directionality": "bidi",
+  "dtype": "float32",
+  "eos_token_id": null,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 768,
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "is_decoder": false,
+  "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",
+  "tie_word_embeddings": true,
+  "transformers_version": "5.0.0",
+  "type_vocab_size": 2,
+  "use_cache": false,
+  "vocab_size": 119547
+}

model.safetensors

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tokenizer_config.json

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+{
+  "backend": "tokenizers",
+  "clean_up_tokenization_spaces": false,
+  "cls_token": "[CLS]",
+  "do_lower_case": false,
+  "is_local": false,
+  "mask_token": "[MASK]",
+  "model_max_length": 512,
+  "model_specific_special_tokens": {},
+  "pad_token": "[PAD]",
+  "sep_token": "[SEP]",
+  "strip_accents": null,
+  "tokenize_chinese_chars": true,
+  "tokenizer_class": "BertTokenizer",
+  "unk_token": "[UNK]"
+}

training_args.bin

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