Model save

README.md

@@ -1,19 +1,54 @@
 ---
-language: en
+library_name: transformers
 license: mit
+base_model: nlpie/tiny-clinicalbert
 tags:
-- question-answering
-- pytorch
-- bert
-datasets:
-- rajpurkar/squad_v2
-- Eladio/emrqa-msquad
+- generated_from_trainer
+model-index:
+- name: tiny-clinicalbert-qa
+  results: []
 ---
 
-<!-- This README.md file is used to generate the README on https://huggingface.co/jon-t/tiny-clinicalbert-qa -->
+<!-- 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-clinicalbert-qa
 
-A lightweight, domain-adapted BERT model for clinical question answering, trained on a combination of [SQuAD v2](https://huggingface.co/datasets/rajpurkar/squad_v2) and [EMRQA-MSQuAD](https://huggingface.co/datasets/Eladio/emrqa-msquad) datasets.
+This model is a fine-tuned version of [nlpie/tiny-clinicalbert](https://huggingface.co/nlpie/tiny-clinicalbert) on the None dataset.
 
-Source code for the training script is available [on GitHub](https://github.com/jon-edward/tiny-clinicalbert-qa). See [eval_results.json](https://huggingface.co/jon-t/tiny-clinicalbert-qa/blob/main/eval_results.json) for evaluation results, and [train_results.json](https://huggingface.co/jon-t/tiny-clinicalbert-qa/blob/main/train_results.json) for training results.
+## 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: 3e-05
+- train_batch_size: 16
+- eval_batch_size: 8
+- seed: 42
+- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_steps: 500
+- num_epochs: 5.0
+
+### Training results
+
+
+
+### Framework versions
+
+- Transformers 4.53.0
+- Pytorch 2.7.1+cu118
+- Datasets 3.6.0
+- Tokenizers 0.21.2

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