End of training

README.md

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+---
+license: mit
+base_model: MoritzLaurer/DeBERTa-v3-large-mnli-fever-anli-ling-wanli
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+model-index:
+- name: 10k-finetune
+  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. -->
+
+# 10k-finetune
+
+This model is a fine-tuned version of [MoritzLaurer/DeBERTa-v3-large-mnli-fever-anli-ling-wanli](https://huggingface.co/MoritzLaurer/DeBERTa-v3-large-mnli-fever-anli-ling-wanli) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.3357
+- Accuracy: 0.8730
+
+## 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: 5e-06
+- train_batch_size: 2
+- eval_batch_size: 16
+- seed: 42
+- gradient_accumulation_steps: 16
+- total_train_batch_size: 32
+- 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
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 0.4093        | 0.33  | 20   | 0.4616          | 0.8115   |
+| 0.2952        | 0.66  | 40   | 0.3984          | 0.8238   |
+| 0.2775        | 0.99  | 60   | 0.3357          | 0.8730   |
+| 0.1836        | 1.32  | 80   | 0.3674          | 0.8402   |
+| 0.1772        | 1.65  | 100  | 0.3687          | 0.8361   |
+| 0.1502        | 1.98  | 120  | 0.3730          | 0.8443   |
+| 0.1245        | 2.31  | 140  | 0.3966          | 0.8402   |
+| 0.1226        | 2.64  | 160  | 0.3719          | 0.8566   |
+| 0.1166        | 2.98  | 180  | 0.3768          | 0.8484   |
+
+
+### Framework versions
+
+- Transformers 4.35.0
+- Pytorch 2.1.0+cu118
+- Datasets 2.14.6
+- Tokenizers 0.14.1

config.json

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+{
+  "_name_or_path": "MoritzLaurer/DeBERTa-v3-large-mnli-fever-anli-ling-wanli",
+  "architectures": [
+    "DebertaV2ForSequenceClassification"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 1024,
+  "id2label": {
+    "0": "entailment",
+    "1": "neutral",
+    "2": "contradiction"
+  },
+  "initializer_range": 0.02,
+  "intermediate_size": 4096,
+  "label2id": {
+    "contradiction": 2,
+    "entailment": 0,
+    "neutral": 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": 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": "4.35.0",
+  "type_vocab_size": 0,
+  "vocab_size": 128100
+}

model.safetensors

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runs/Nov08_19-39-50_02705521eaac/events.out.tfevents.1699472396.02705521eaac.777.0

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training_args.bin

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