Update README.md

README.md

@@ -1,199 +1,59 @@
 ---
 library_name: transformers
-tags: []
+license: apache-2.0
+language:
+- ja
 ---
 
-# Model Card for Model ID
+# llm-jp-modernbert-base-v4-ja
 
-<!-- Provide a quick summary of what the model is/does. -->
+This model is based on the [modernBERT-base](https://arxiv.org/abs/2412.13663) architecture with [llm-jp-tokenizer](https://github.com/llm-jp/llm-jp-tokenizer).
+It was trained using the Japanese subset (3.4TB) of the llm-jp-corpus v4 and supports a max sequence length of 8192.
 
 
+## Training
 
-## Model Details
+This model was trained with a max_seq_len of 1024 in stage 1, and then with a max_seq_len of 8192 in stage 2.
 
-### Model Description
+| Model              |      stage 1    |    stage 2      |
+|:------------------ |----------------:|----------------:|
+| max_seq_len        | 1024            | 8192            |
+| max_steps          | 500,000         | 200,000         |
+| Total batch size   | 3328            | 384             |
+| Peak LR            | 5e-4            | 5e-5            |
+| warmup step        | 24,000          |                 |
+| LR schedule        | Linear decay    |                 |
+| Adam beta 1        | 0.9             |                 |
+| Adam beta 2        | 0.98            |                 |
+| Adam eps           | 1e-6            |                 |
+| MLM prob           | 0.30            |                 |
+| Gradient clipping  | 1.0             |                 |
+| weight decay       | 1e-5            |                 |
+| line_by_line       | True            |                 |
 
-<!-- Provide a longer summary of what this model is. -->
+The blank in stage 2 indicate the same value as in stage 1.
 
-This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
+In theory, stage 1 consumes 1.7T tokens, but sentences with fewer than 1024 tokens are truncated, so the actual consumption is lower. Stage 2 theoretically consumes 0.6T tokens.
 
-- **Developed by:** [More Information Needed]
-- **Funded by [optional]:** [More Information Needed]
-- **Shared by [optional]:** [More Information Needed]
-- **Model type:** [More Information Needed]
-- **Language(s) (NLP):** [More Information Needed]
-- **License:** [More Information Needed]
-- **Finetuned from model [optional]:** [More Information Needed]
-
-### Model Sources [optional]
-
-<!-- Provide the basic links for the model. -->
-
-- **Repository:** [More Information Needed]
-- **Paper [optional]:** [More Information Needed]
-- **Demo [optional]:** [More Information Needed]
-
-## Uses
-
-<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
-
-### Direct Use
-
-<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
-
-[More Information Needed]
-
-### Downstream Use [optional]
-
-<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
-
-[More Information Needed]
-
-### Out-of-Scope Use
-
-<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
-
-[More Information Needed]
-
-## Bias, Risks, and Limitations
-
-<!-- This section is meant to convey both technical and sociotechnical limitations. -->
-
-[More Information Needed]
-
-### Recommendations
-
-<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
-
-Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
-
-## How to Get Started with the Model
-
-Use the code below to get started with the model.
-
-[More Information Needed]
-
-## Training Details
-
-### Training Data
-
-<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
-
-[More Information Needed]
-
-### Training Procedure
-
-<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
-
-#### Preprocessing [optional]
-
-[More Information Needed]
-
-
-#### Training Hyperparameters
-
-- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
-
-#### Speeds, Sizes, Times [optional]
-
-<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
-
-[More Information Needed]
+For reference, Warner et al.'s ModernBERT uses 1.72T tokens for stage 1, 250B tokens for stage 2, and 50B tokens for stage 3.
 
 ## Evaluation
 
-<!-- This section describes the evaluation protocols and provides the results. -->
-
-### Testing Data, Factors & Metrics
-
-#### Testing Data
-
-<!-- This should link to a Dataset Card if possible. -->
-
-[More Information Needed]
-
-#### Factors
-
-<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
-
-[More Information Needed]
-
-#### Metrics
-
-<!-- These are the evaluation metrics being used, ideally with a description of why. -->
-
-[More Information Needed]
-
-### Results
-
-[More Information Needed]
-
-#### Summary
-
-
-
-## Model Examination [optional]
-
-<!-- Relevant interpretability work for the model goes here -->
-
-[More Information Needed]
-
-## Environmental Impact
-
-<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
-
-Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
-
-- **Hardware Type:** [More Information Needed]
-- **Hours used:** [More Information Needed]
-- **Cloud Provider:** [More Information Needed]
-- **Compute Region:** [More Information Needed]
-- **Carbon Emitted:** [More Information Needed]
-
-## Technical Specifications [optional]
-
-### Model Architecture and Objective
-
-[More Information Needed]
-
-### Compute Infrastructure
-
-[More Information Needed]
-
-#### Hardware
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-[More Information Needed]
-
-#### Software
-
-[More Information Needed]
-
-## Citation [optional]
-
-<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
-
-**BibTeX:**
-
-[More Information Needed]
-
-**APA:**
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-[More Information Needed]
-
-## Glossary [optional]
-
-<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
-
-[More Information Needed]
-
-## More Information [optional]
-
-[More Information Needed]
+For the sentence classification task evaluation, the datasets JSTS, JNLI, and JCoLA from [JGLUE](https://aclanthology.org/2022.lrec-1.317/) were used. For the evaluation of the Zero-shot Sentence Retrieval task, the [miracl/miracl](https://huggingface.co/datasets/miracl/miracl) dataset (ja subset) was used.
+Evaluation code can be found at https://github.com/speed1313/bert-eval
 
-## Model Card Authors [optional]
+| Model                                          |   JSTS |   JNLI |   JCoLA |   Avg(JGLUE) | miracl   |    Avg |
+|------------------------------------------------|--------|--------|---------|--------------|----------|--------|
+| tohoku-nlp/bert-base-japanese-v3               | 0.9196 | 0.9117 |  0.8798 |       0.9037 | 0.74     | 0.8628 |
+| sbintuitions/modernbert-ja-130m                | 0.9159 | 0.9273 |  0.8682 |       0.9038 | 0.5069   | 0.8046 |
+| sbintuitions/modernbert-ja-310m                | 0.9317 | 0.9326 |  0.8832 |       0.9158 | 0.6569   | 0.8511 |
+| llm-jp-modernbert-base-v3-stage1-500k   | 0.9247 | 0.917  |  0.8555 |       0.8991 | 0.5515   | 0.8122 |
+| llm-jp-modernbert-base-v3-stage2-200k   | 0.9238 | 0.9108 |  0.8439 |       0.8928 | 0.5384   | 0.8042 |
+| llm-jp-modernbert-base-v4-ja-stage1-100k | 0.9213 | 0.9182 |  0.8613 |       0.9003 | N/A      | N/A |
+| llm-jp-modernbert-base-v4-ja-stage1-300k | 0.9199 | 0.9187 |  0.852  |       0.8969 | N/A      | N/A |
+| llm-jp-modernbert-base-v4-ja-stage1-400k | 0.9214 | 0.9203 |  0.8555 |       0.8991 | N/A      | N/A |
+| llm-jp-modernbert-base-v4-ja-stage1-500k | 0.9212 | 0.9195 |  0.8451 |       0.8953 | 0.6025   | 0.8221 |
+| llm-jp-modernbert-base-v4-ja-stage2-200k | 0.9177 | 0.9133 |  0.8439 |       0.8916 | 0.5739   | 0.8122 |
 
-[More Information Needed]
 
-## Model Card Contact
 
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