Upload final checkpoint

README.md

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+---
+library_name: transformers
+license: mit
+base_model: MoritzLaurer/deberta-v3-large-zeroshot-v2.0
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+model-index:
+- name: results
+  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. -->
+
+# results
+
+This model is a fine-tuned version of [MoritzLaurer/deberta-v3-large-zeroshot-v2.0](https://huggingface.co/MoritzLaurer/deberta-v3-large-zeroshot-v2.0) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.2757
+- Accuracy: 0.8113
+- F1 Macro: 0.7264
+- Precision Neutral: 0.8559
+- Recall Neutral: 0.8920
+- F1 Neutral: 0.8736
+- Support Neutral: 213
+- Precision Entailment: 0.7436
+- Recall Entailment: 0.5472
+- F1 Entailment: 0.6304
+- Support Entailment: 53
+- Precision Contradiction: 0.6341
+- Recall Contradiction: 0.7222
+- F1 Contradiction: 0.6753
+- Support Contradiction: 36
+
+## 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: 1e-05
+- train_batch_size: 32
+- eval_batch_size: 128
+- seed: 42
+- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
+- lr_scheduler_type: linear
+- num_epochs: 4
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Macro | Precision Neutral | Recall Neutral | F1 Neutral | Support Neutral | Precision Entailment | Recall Entailment | F1 Entailment | Support Entailment | Precision Contradiction | Recall Contradiction | F1 Contradiction | Support Contradiction |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:-----------------:|:--------------:|:----------:|:---------------:|:--------------------:|:-----------------:|:-------------:|:------------------:|:-----------------------:|:--------------------:|:----------------:|:---------------------:|
+| 0.0311        | 1.0   | 383  | 0.2757          | 0.8113   | 0.7264   | 0.8559            | 0.8920         | 0.8736     | 213             | 0.7436               | 0.5472            | 0.6304        | 53                 | 0.6341                  | 0.7222               | 0.6753           | 36                    |
+| 0.0179        | 2.0   | 766  | 0.3661          | 0.7781   | 0.6858   | 0.8387            | 0.8545         | 0.8465     | 213             | 0.6226               | 0.6226            | 0.6226        | 53                 | 0.625                   | 0.5556               | 0.5882           | 36                    |
+| 0.003         | 3.0   | 1149 | 0.4953          | 0.8013   | 0.7063   | 0.8341            | 0.8967         | 0.8643     | 213             | 0.7045               | 0.5849            | 0.6392        | 53                 | 0.6897                  | 0.5556               | 0.6154           | 36                    |
+| 0.0008        | 4.0   | 1532 | 0.5224          | 0.7980   | 0.6984   | 0.8341            | 0.8967         | 0.8643     | 213             | 0.6977               | 0.5660            | 0.625         | 53                 | 0.6667                  | 0.5556               | 0.6061           | 36                    |
+
+
+### Framework versions
+
+- Transformers 4.51.3
+- Pytorch 2.6.0+cu124
+- Datasets 3.5.1
+- Tokenizers 0.21.1

added_tokens.json

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+}

config.json

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+{
+  "architectures": [
+    "DebertaV2ForSequenceClassification"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 1024,
+  "id2label": {
+    "0": "LABEL_0",
+    "1": "LABEL_1",
+    "2": "LABEL_2"
+  },
+  "initializer_range": 0.02,
+  "intermediate_size": 4096,
+  "label2id": {
+    "LABEL_0": 0,
+    "LABEL_1": 1,
+    "LABEL_2": 2
+  },
+  "layer_norm_eps": 1e-07,
+  "legacy": true,
+  "max_position_embeddings": 512,
+  "max_relative_positions": -1,
+  "model_type": "deberta-v2",
+  "norm_rel_ebd": "layer_norm",
+  "num_attention_heads": 16,
+  "num_hidden_layers": 24,
+  "pad_token_id": 0,
+  "pooler_dropout": 0,
+  "pooler_hidden_act": "gelu",
+  "pooler_hidden_size": 1024,
+  "pos_att_type": [
+    "p2c",
+    "c2p"
+  ],
+  "position_biased_input": false,
+  "position_buckets": 256,
+  "relative_attention": true,
+  "share_att_key": true,
+  "torch_dtype": "float32",
+  "transformers_version": "4.51.3",
+  "type_vocab_size": 0,
+  "vocab_size": 128100
+}

model.safetensors

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special_tokens_map.json

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tokenizer_config.json

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+  "pad_token": "[PAD]",
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+  "sp_model_kwargs": {},
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+  "tokenizer_class": "DebertaV2Tokenizer",
+  "unk_token": "[UNK]",
+  "vocab_type": "spm"
+}

training_args.bin

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