cglez
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bert-imdb-uncased

@@ -1,199 +1,96 @@
 ---
 library_name: transformers
-tags: []
 ---
-# Model Card for Model ID
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 ## Model Details
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-This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
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 ---
 library_name: transformers
+language: en
+license: apache-2.0
+datasets:
+- stanfordnlp/imdb
+base_model:
+- google-bert/bert-base-uncased
 ---
+# Model Card: BERT-IMDb
+An in-domain BERT-base model, pre-trained from scratch on the IMDb dataset text.
 ## Model Details
+### Description
+This model is based on the [BERT base (uncased)](https://huggingface.co/google-bert/bert-base-uncased)
+architecture and was pre-trained from scratch (in-domain) using the text in IMDb dataset, excluding its test split.
+Only the masked language modeling (MLM) objective was used during pre-training.
+- **Developed by:** [Cesar Gonzalez-Gutierrez](https://ceguel.es)
+- **Funded by:** [ERC](https://erc.europa.eu)
+- **Architecture:** BERT-base
+- **Language:** English
+- **License:** Apache 2.0
+- **Base model:** [BERT base model (uncased)](https://huggingface.co/google-bert/bert-base-uncased)
+### Checkpoints
+Intermediate checkpoints from the pre-training process are available and can be accessed using specific tags,
+which correspond to training epochs and steps:
+| Epoch | Step | Tags | |
+|---|---|---|---|
+| 1 | 703 | epoch-1 | step-703 |
+| 5 | 3516 | epoch-5 | step-3516 |
+| 10 | 7033 | epoch-10 | step-7033 |
+| 20 | 14066 | epoch-20 | step-14066 |
+| 30 | 21100 | epoch-30 | step-21100 |
+| 40 | 28133 | epoch-40 | step-28133 |
+| 50 | 35166 | epoch-50 | step-35166 |
+| 60 | 42200 | epoch-60 | step-42200 |
+| 70 | 49233 | epoch-70 | step-49233 |
+| 80 | 56240 | epoch-80 | step-56240 |
+To load a model from a specific intermediate checkpoint, use the `revision` parameter with the corresponding tag:
+```python
+from transformers import AutoModelForMaskedLM
+model = AutoModelForMaskedLM.from_pretrained("<model-name>", revision="<checkpoint-tag>")
+```
+### Sources
+- **Paper:** [Information pending]
 ## Training Details
+For more details on the training procedure, please refer to the base model's documentation:
+[Training procedure](https://huggingface.co/google-bert/bert-base-uncased#training-procedure).
+### Training Data
+All texts from IMDb dataset, excluding the test partition.
 #### Training Hyperparameters
+- **Precision:** fp16
+- **Batch size:** 32
+- **Gradient accumulation steps:** 3
+## Uses
+For typical use cases and limitations, please refer to the base model's guidance:
+[Inteded uses & limitations](https://huggingface.co/google-bert/bert-base-uncased#intended-uses--limitations).
+## Bias, Risks, and Limitations
+This model inherits potential risks and limitations from the base model. Refer to:
+[Limitations and bias](https://huggingface.co/google-bert/bert-base-uncased#limitations-and-bias).
 ## Environmental Impact
+- **Hardware Type:** NVIDIA Tesla V100 PCIE 32GB
+- **Runtime:** 11.5
+- **Cluster Provider:** [Artemisa](https://artemisa.ific.uv.es/web/)
+- **Compute Region:** EU
+- **Carbon Emitted:** 2.14 kg CO2 eq.
+## Citation
 **BibTeX:**
 [More Information Needed]