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README.md
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README.md
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---
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library_name: transformers
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license: apache-2.0
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base_model: answerdotai/ModernBERT-base
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tags:
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- generated_from_trainer
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metrics:
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- accuracy
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model-index:
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- name: ModernBERT-base-zeroshot-v2.0
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results: []
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---
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# ModernBERT-base-zeroshot-v2.0
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ModernBERT-base-zeroshot-v2.0
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## Model description
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This model is [answerdotai/ModernBERT-base](https://huggingface.co/answerdotai/ModernBERT-base)
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fine-tuned on the same dataset mix as the `zeroshot-v2.0` models in the [Zeroshot Classifiers Collection](https://huggingface.co/collections/MoritzLaurer/zeroshot-classifiers-6548b4ff407bb19ff5c3ad6f).
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## General takeaways:
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- The model is very fast and memory efficient. It's multiple times faster and consumes multiple times less memory than DeBERTav3.
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The memory efficiency enables larger batch sizes. I got a ~2x speed increase by enabling bf16 (instead of fp16).
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- It performs slightly worse then DeBERTav3 on average on the tasks tested below.
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- I'm in the process of preparing a newer version trained on better synthetic data to make full use of the 8k context window
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and to update the training mix of the older `zeroshot-v2.0` models.
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## Training results
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Per-dataset breakdown:
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|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|
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| :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: |
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|Accuracy|0.831|0.835|0.932|0.936|0.884|0.763|0.647|0.657|0.823|0.889|0.753|0.864|0.949|0.935|0.974|0.798|0.788|0.727|0.789|0.793|0.489|0.893|0.717|0.927|0.851|0.859|0.907|0.952|0.926|0.726|0.978|0.912|0.914|0.93|0.951|0.906|0.476|0.708|
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|F1 macro|0.813|0.818|0.925|0.93|0.872|0.74|0.61|0.611|0.81|0.874|0.751|0.864|0.949|0.935|0.974|0.751|0.738|0.746|0.733|0.798|0.475|0.893|0.712|0.919|0.851|0.859|0.892|0.952|0.847|0.721|0.966|0.912|0.914|0.93|0.942|0.906|0.329|0.637|
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|Inference text/sec (A100 40GB GPU, batch=128)|3472.0|3474.0|2338.0|4416.0|2993.0|2959.0|2904.0|3003.0|4647.0|4486.0|5032.0|4354.0|2466.0|1140.0|1582.0|4392.0|5446.0|5296.0|4904.0|4787.0|2251.0|4042.0|1884.0|4048.0|4032.0|4121.0|4275.0|3746.0|4485.0|1114.0|4322.0|2260.0|2274.0|2189.0|2085.0|2410.0|3933.0|4388.0|
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## Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 5e-05
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- train_batch_size: 32
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- eval_batch_size: 128
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- seed: 42
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- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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- lr_scheduler_type: linear
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- lr_scheduler_warmup_ratio: 0.06
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- num_epochs: 2
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## Framework versions
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- Transformers 4.48.0.dev0
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- Pytorch 2.5.1+cu124
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- Datasets 3.2.0
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- Tokenizers 0.21.0
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"_name_or_path": "answerdotai/ModernBERT-base",
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"architectures": [
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"ModernBertForSequenceClassification"
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],
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"attention_bias": false,
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"attention_dropout": 0.0,
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"bos_token_id": 50281,
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"classifier_activation": "gelu",
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"classifier_bias": false,
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"classifier_dropout": 0.0,
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"classifier_pooling": "mean",
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"cls_token_id": 50281,
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"decoder_bias": true,
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"deterministic_flash_attn": false,
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"embedding_dropout": 0.0,
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"eos_token_id": 50282,
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"global_attn_every_n_layers": 3,
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"global_rope_theta": 160000.0,
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"gradient_checkpointing": false,
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"hidden_activation": "gelu",
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"hidden_size": 768,
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"id2label": {
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"0": "entailment",
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"1": "not_entailment"
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},
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"initializer_cutoff_factor": 2.0,
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"initializer_range": 0.02,
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"intermediate_size": 1152,
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"label2id": {
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"entailment": 0,
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"not_entailment": 1
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},
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"layer_norm_eps": 1e-05,
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"local_attention": 128,
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"local_rope_theta": 10000.0,
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"max_position_embeddings": 8192,
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"mlp_bias": false,
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"mlp_dropout": 0.0,
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"model_type": "modernbert",
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"norm_bias": false,
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"norm_eps": 1e-05,
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"num_attention_heads": 12,
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"num_hidden_layers": 22,
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"pad_token_id": 50283,
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"position_embedding_type": "absolute",
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"problem_type": "single_label_classification",
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"reference_compile": true,
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"sep_token_id": 50282,
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"sparse_pred_ignore_index": -100,
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"sparse_prediction": false,
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"torch_dtype": "bfloat16",
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"transformers_version": "4.48.0.dev0",
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"vocab_size": 50368
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}
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|
||||
"50365": {
|
||||
"content": "[unused80]",
|
||||
"lstrip": false,
|
||||
"normalized": true,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"50366": {
|
||||
"content": "[unused81]",
|
||||
"lstrip": false,
|
||||
"normalized": true,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"50367": {
|
||||
"content": "[unused82]",
|
||||
"lstrip": false,
|
||||
"normalized": true,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
}
|
||||
},
|
||||
"clean_up_tokenization_spaces": true,
|
||||
"cls_token": "[CLS]",
|
||||
"extra_special_tokens": {},
|
||||
"mask_token": "[MASK]",
|
||||
"model_input_names": [
|
||||
"input_ids",
|
||||
"attention_mask"
|
||||
],
|
||||
"model_max_length": 512,
|
||||
"pad_token": "[PAD]",
|
||||
"sep_token": "[SEP]",
|
||||
"tokenizer_class": "PreTrainedTokenizerFast",
|
||||
"unk_token": "[UNK]"
|
||||
}
|
||||
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Reference in New Issue