---
library_name: transformers
license: apache-2.0
base_model: answerdotai/ModernBERT-large
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: ModernBERT-large-zeroshot-v2.0-2024-12-28-00-13
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# ModernBERT-large-zeroshot-v2.0-2024-12-28-00-13

This model is a fine-tuned version of [answerdotai/ModernBERT-large](https://huggingface.co./answerdotai/ModernBERT-large) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1803
- F1 Macro: 0.6624
- F1 Micro: 0.7304
- Accuracy Balanced: 0.6979
- Accuracy: 0.7304
- Precision Macro: 0.6899
- Recall Macro: 0.6979
- Precision Micro: 0.7304
- Recall Micro: 0.7304

## 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: 9e-06
- train_batch_size: 16
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Use 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_ratio: 0.06
- num_epochs: 2

### Training results

| Training Loss | Epoch  | Step  | Validation Loss | F1 Macro | F1 Micro | Accuracy Balanced | Accuracy | Precision Macro | Recall Macro | Precision Micro | Recall Micro |
|:-------------:|:------:|:-----:|:---------------:|:--------:|:--------:|:-----------------:|:--------:|:---------------:|:------------:|:---------------:|:------------:|
| 0.3865        | 1.0    | 33915 | 0.3321          | 0.8584   | 0.8704   | 0.8600            | 0.8704   | 0.8569          | 0.8600       | 0.8704          | 0.8704       |
| 0.2456        | 2.0000 | 67828 | 0.4069          | 0.8600   | 0.8728   | 0.8590            | 0.8728   | 0.8610          | 0.8590       | 0.8728          | 0.8728       |


Breakdown by dataset

|Datasets|Mean|Mean w/o NLI|mnli_m|mnli_mm|fevernli|anli_r1|anli_r2|anli_r3|wanli|lingnli|wellformedquery|rottentomatoes|amazonpolarity|imdb|yelpreviews|hatexplain|massive|banking77|emotiondair|emocontext|empathetic|agnews|yahootopics|biasframes_sex|biasframes_offensive|biasframes_intent|financialphrasebank|appreviews|hateoffensive|trueteacher|spam|wikitoxic_toxicaggregated|wikitoxic_obscene|wikitoxic_identityhate|wikitoxic_threat|wikitoxic_insult|manifesto|capsotu|
| :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: |
|Accuracy|0.85|0.851|0.942|0.944|0.894|0.812|0.717|0.716|0.836|0.909|0.815|0.899|0.964|0.951|0.984|0.814|0.8|0.744|0.752|0.802|0.544|0.899|0.735|0.934|0.864|0.877|0.913|0.953|0.921|0.821|0.989|0.901|0.927|0.931|0.959|0.911|0.497|0.73|
|F1 macro|0.834|0.835|0.935|0.938|0.882|0.795|0.688|0.676|0.823|0.898|0.814|0.899|0.964|0.951|0.984|0.77|0.753|0.763|0.69|0.805|0.533|0.899|0.729|0.925|0.864|0.877|0.901|0.953|0.855|0.821|0.983|0.901|0.927|0.931|0.952|0.911|0.362|0.662|
|Inference text/sec (GPU, batch=32)|1116.0|1104.0|1039.0|1241.0|1138.0|1102.0|1124.0|1133.0|1251.0|1240.0|1263.0|1231.0|1054.0|559.0|795.0|1238.0|1312.0|1285.0|1273.0|1268.0|992.0|1222.0|894.0|1176.0|1194.0|1197.0|1206.0|1166.0|1227.0|541.0|1199.0|1045.0|1054.0|1020.0|1005.0|1063.0|1214.0|1220.0|



### Framework versions

- Transformers 4.48.0.dev0
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0