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--- |
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license: apache-2.0 |
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tags: |
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- generated_from_keras_callback |
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model-index: |
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- name: MUmairAB/bert-based-MaskedLM |
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results: [] |
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datasets: |
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- imdb |
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pipeline_tag: fill-mask |
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--- |
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<!-- This model card has been generated automatically according to the information Keras had access to. You should |
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probably proofread and complete it, then remove this comment. --> |
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# MUmairAB/bert-based-MaskedLM |
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This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on [IMDB Movies Review](https://huggingface.co/datasets/imdb) dataset. |
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It achieves the following results on the evaluation set: |
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- Train Loss: 2.4360 |
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- Validation Loss: 2.3284 |
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- Epoch: 20 |
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## Model description |
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[DistilBERT-base-uncased](https://huggingface.co/distilbert-base-uncased) |
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``` |
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Model: "tf_distil_bert_for_masked_lm" |
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_________________________________________________________________ |
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Layer (type) Output Shape Param # |
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================================================================= |
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distilbert (TFDistilBertMai multiple 66362880 |
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nLayer) |
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vocab_transform (Dense) multiple 590592 |
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vocab_layer_norm (LayerNorm multiple 1536 |
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alization) |
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vocab_projector (TFDistilBe multiple 23866170 |
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rtLMHead) |
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================================================================= |
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Total params: 66,985,530 |
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Trainable params: 66,985,530 |
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Non-trainable params: 0 |
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_________________________________________________________________ |
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``` |
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## Intended uses & limitations |
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The model was trained on IMDB movies review dataset. So, it inherits the language biases from the dataset. |
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## Training and evaluation data |
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The model was trained on [IMDB Movies Review](https://huggingface.co/datasets/imdb) dataset. |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- optimizer: {'name': 'AdamWeightDecay', 'learning_rate': {'class_name': 'WarmUp', 'config': {'initial_learning_rate': 2e-05, 'decay_schedule_fn': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': -60, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, '__passive_serialization__': True}, 'warmup_steps': 1000, 'power': 1.0, 'name': None}}, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False, 'weight_decay_rate': 0.01} |
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- training_precision: float32 |
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### Training results |
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| Train Loss | Validation Loss | Epoch | |
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|:----------:|:---------------:|:-----:| |
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| 3.0754 | 2.7548 | 0 | |
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| 2.7969 | 2.6209 | 1 | |
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| 2.7214 | 2.5588 | 2 | |
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| 2.6626 | 2.5554 | 3 | |
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| 2.6466 | 2.4881 | 4 | |
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| 2.6238 | 2.4775 | 5 | |
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| 2.5696 | 2.4280 | 6 | |
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| 2.5504 | 2.3924 | 7 | |
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| 2.5171 | 2.3725 | 8 | |
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| 2.5180 | 2.3142 | 9 | |
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| 2.4443 | 2.2974 | 10 | |
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| 2.4497 | 2.3317 | 11 | |
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| 2.4371 | 2.3317 | 12 | |
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| 2.4377 | 2.3237 | 13 | |
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| 2.4369 | 2.3338 | 14 | |
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| 2.4350 | 2.3021 | 15 | |
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| 2.4267 | 2.3264 | 16 | |
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| 2.4557 | 2.3280 | 17 | |
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| 2.4461 | 2.3165 | 18 | |
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| 2.4360 | 2.3284 | 19 | |
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### Framework versions |
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- Transformers 4.30.2 |
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- TensorFlow 2.12.0 |
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- Tokenizers 0.13.3 |
