End of training

README-deberta-v3-base-zeroshot-v1.1-all-33-20240109.md

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+
+Model Card
+==========

README.md

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+---
+license: mit
+base_model: MoritzLaurer/deberta-v3-base-zeroshot-v1.1-all-33
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+model-index:
+- name: zeroshot-classification-test4
+  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. -->
+
+# zeroshot-classification-test4
+
+This model is a fine-tuned version of [MoritzLaurer/deberta-v3-base-zeroshot-v1.1-all-33](https://huggingface.co/MoritzLaurer/deberta-v3-base-zeroshot-v1.1-all-33) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.4552
+- F1 Macro: 0.8589
+- F1 Micro: 0.859
+- Accuracy Balanced: 0.8590
+- Accuracy: 0.859
+- Precision Macro: 0.8596
+- Recall Macro: 0.8590
+- Precision Micro: 0.859
+- Recall Micro: 0.859
+
+## 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: 2e-05
+- train_batch_size: 32
+- 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_ratio: 0.06
+- num_epochs: 3
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | F1 Macro | F1 Micro | Accuracy Balanced | Accuracy | Precision Macro | Recall Macro | Precision Micro | Recall Micro |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:-----------------:|:--------:|:---------------:|:------------:|:---------------:|:------------:|
+| No log        | 1.0   | 313  | 0.3407          | 0.8507   | 0.851    | 0.8509            | 0.851    | 0.8534          | 0.8509       | 0.851           | 0.851        |
+| 0.373         | 2.0   | 626  | 0.3830          | 0.8600   | 0.86     | 0.8600            | 0.86     | 0.86            | 0.8600       | 0.86            | 0.86         |
+| 0.373         | 3.0   | 939  | 0.4552          | 0.8589   | 0.859    | 0.8590            | 0.859    | 0.8596          | 0.8590       | 0.859           | 0.859        |
+
+
+### Framework versions
+
+- Transformers 4.37.2
+- Pytorch 2.2.0+cu121
+- Datasets 2.16.1
+- Tokenizers 0.15.1

added_tokens.json

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best-deberta-v3-base-zeroshot-v1.1-all-33-20240109/added_tokens.json

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best-deberta-v3-base-zeroshot-v1.1-all-33-20240109/config.json

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+  "_name_or_path": "MoritzLaurer/deberta-v3-base-zeroshot-v1.1-all-33",
+  "architectures": [
+    "DebertaV2ForSequenceClassification"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 768,
+  "id2label": {
+    "0": "entailment",
+    "1": "not_entailment"
+  },
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "label2id": {
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+    "not_entailment": 1
+  },
+  "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": 12,
+  "num_hidden_layers": 12,
+  "pad_token_id": 0,
+  "pooler_dropout": 0,
+  "pooler_hidden_act": "gelu",
+  "pooler_hidden_size": 768,
+  "pos_att_type": [
+    "p2c",
+    "c2p"
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+  "position_buckets": 256,
+  "relative_attention": true,
+  "share_att_key": true,
+  "torch_dtype": "float32",
+  "transformers_version": "4.37.2",
+  "type_vocab_size": 0,
+  "vocab_size": 128100
+}

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