metadata
license: apache-2.0
tags:
- generated_from_keras_callback
datasets:
- imdb
pipeline_tag: fill-mask
base_model: distilbert-base-uncased
model-index:
- name: MUmairAB/bert-based-MaskedLM
results: []
MUmairAB/bert-based-MaskedLM
The model training code is available as a notebook on my GitHub
This model is a fine-tuned version of distilbert-base-uncased on IMDB Movies Review dataset. It achieves the following results on the evaluation set:
- Train Loss: 2.4360
- Validation Loss: 2.3284
- Epoch: 20
Training and validation loss during training
Model description
DistilBERT-base-uncased ``` Model: "tf_distil_bert_for_masked_lm" _________________________________________________________________ Layer (type) Output Shape Param #
distilbert (TFDistilBertMai multiple 66362880
nLayer)
vocab_transform (Dense) multiple 590592
vocab_layer_norm (LayerNorm multiple 1536
alization)
vocab_projector (TFDistilBe multiple 23866170
rtLMHead)
Total params: 66,985,530 Trainable params: 66,985,530 Non-trainable params: 0
## Intended uses & limitations
The model was trained on IMDB movies review dataset. So, it inherits the language biases from the dataset.
## Training and evaluation data
The model was trained on [IMDB Movies Review](https://huggingface.co/datasets/imdb) dataset.
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- 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}
- training_precision: float32
### Training results
| Train Loss | Validation Loss | Epoch |
|:----------:|:---------------:|:-----:|
| 3.0754 | 2.7548 | 0 |
| 2.7969 | 2.6209 | 1 |
| 2.7214 | 2.5588 | 2 |
| 2.6626 | 2.5554 | 3 |
| 2.6466 | 2.4881 | 4 |
| 2.6238 | 2.4775 | 5 |
| 2.5696 | 2.4280 | 6 |
| 2.5504 | 2.3924 | 7 |
| 2.5171 | 2.3725 | 8 |
| 2.5180 | 2.3142 | 9 |
| 2.4443 | 2.2974 | 10 |
| 2.4497 | 2.3317 | 11 |
| 2.4371 | 2.3317 | 12 |
| 2.4377 | 2.3237 | 13 |
| 2.4369 | 2.3338 | 14 |
| 2.4350 | 2.3021 | 15 |
| 2.4267 | 2.3264 | 16 |
| 2.4557 | 2.3280 | 17 |
| 2.4461 | 2.3165 | 18 |
| 2.4360 | 2.3284 | 19 |
### Framework versions
- Transformers 4.30.2
- TensorFlow 2.12.0
- Tokenizers 0.13.3