deberta-v3-xsmall-beavertails-harmful-qa-classifier

README.md

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+---
+license: mit
+base_model: microsoft/deberta-v3-xsmall
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+model-index:
+- name: deberta-v3-xsmall-beavertails-harmful-qa-classifier
+  results: []
+---
+
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
+
+# deberta-v3-xsmall-beavertails-harmful-qa-classifier
+
+This model is a fine-tuned version of [microsoft/deberta-v3-xsmall](https://huggingface.co/microsoft/deberta-v3-xsmall) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.3043
+- Accuracy: 0.8716
+- Macro F1: 0.8716
+- Macro Precision: 0.8738
+- Macro Recall: 0.8736
+- Micro F1: 0.8716
+- Micro Precision: 0.8716
+- Micro Recall: 0.8716
+
+## 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: 6e-06
+- train_batch_size: 128
+- eval_batch_size: 128
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_steps: 1000
+- num_epochs: 4
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | Macro F1 | Macro Precision | Macro Recall | Micro F1 | Micro Precision | Micro Recall |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:---------------:|:------------:|:--------:|:---------------:|:------------:|
+| 0.3726        | 1.0   | 2349 | 0.3409          | 0.8573   | 0.8573   | 0.8581          | 0.8587       | 0.8573   | 0.8573          | 0.8573       |
+| 0.3299        | 2.0   | 4698 | 0.3186          | 0.8669   | 0.8669   | 0.8697          | 0.8692       | 0.8669   | 0.8669          | 0.8669       |
+| 0.3181        | 3.0   | 7047 | 0.3092          | 0.8683   | 0.8682   | 0.8715          | 0.8707       | 0.8683   | 0.8683          | 0.8683       |
+| 0.3064        | 4.0   | 9396 | 0.3043          | 0.8716   | 0.8716   | 0.8738          | 0.8736       | 0.8716   | 0.8716          | 0.8716       |
+
+
+### Framework versions
+
+- Transformers 4.40.0
+- Pytorch 2.2.2+cu121
+- Datasets 2.19.0
+- Tokenizers 0.19.1

added_tokens.json

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+{
+  "[MASK]": 128000
+}

config.json

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+{
+  "_name_or_path": "microsoft/deberta-v3-xsmall",
+  "architectures": [
+    "DebertaV2ForSequenceClassification"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 384,
+  "initializer_range": 0.02,
+  "intermediate_size": 1536,
+  "layer_norm_eps": 1e-07,
+  "max_position_embeddings": 512,
+  "max_relative_positions": -1,
+  "model_type": "deberta-v2",
+  "norm_rel_ebd": "layer_norm",
+  "num_attention_heads": 6,
+  "num_hidden_layers": 12,
+  "pad_token_id": 0,
+  "pooler_dropout": 0,
+  "pooler_hidden_act": "gelu",
+  "pooler_hidden_size": 384,
+  "pos_att_type": [
+    "p2c",
+    "c2p"
+  ],
+  "position_biased_input": false,
+  "position_buckets": 256,
+  "relative_attention": true,
+  "share_att_key": true,
+  "torch_dtype": "float32",
+  "transformers_version": "4.40.0",
+  "type_vocab_size": 0,
+  "vocab_size": 128100
+}

model.safetensors

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special_tokens_map.json

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+  "cls_token": "[CLS]",
+  "eos_token": "[SEP]",
+  "mask_token": "[MASK]",
+  "pad_token": "[PAD]",
+  "sep_token": "[SEP]",
+  "unk_token": {
+    "content": "[UNK]",
+    "lstrip": false,
+    "normalized": true,
+    "rstrip": false,
+    "single_word": false
+  }
+}

spm.model

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tokenizer_config.json

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+{
+  "added_tokens_decoder": {
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+      "content": "[PAD]",
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+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
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+      "lstrip": false,
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+      "single_word": false,
+      "special": true
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+  "bos_token": "[CLS]",
+  "clean_up_tokenization_spaces": true,
+  "cls_token": "[CLS]",
+  "do_lower_case": false,
+  "eos_token": "[SEP]",
+  "mask_token": "[MASK]",
+  "model_max_length": 1000000000000000019884624838656,
+  "pad_token": "[PAD]",
+  "sep_token": "[SEP]",
+  "sp_model_kwargs": {},
+  "split_by_punct": false,
+  "tokenizer_class": "DebertaV2Tokenizer",
+  "unk_token": "[UNK]",
+  "vocab_type": "spm"
+}

training_args.bin

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