End of training

README.md

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+---
+library_name: transformers
+license: mit
+base_model: microsoft/deberta-v3-large
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- precision
+- recall
+- f1
+model-index:
+- name: panclef_data_deberta_finetuned
+  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. -->
+
+# panclef_data_deberta_finetuned
+
+This model is a fine-tuned version of [microsoft/deberta-v3-large](https://huggingface.co/microsoft/deberta-v3-large) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.1185
+- Accuracy: 0.9728
+- Precision: 0.9735
+- Recall: 0.9728
+- F1: 0.9729
+
+## 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: 3e-05
+- train_batch_size: 32
+- eval_batch_size: 32
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 10
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
+| 0.3364        | 1.0   | 556  | 0.1755          | 0.9550   | 0.9572    | 0.9550 | 0.9552 |
+| 0.2607        | 2.0   | 1112 | 0.2262          | 0.9347   | 0.9379    | 0.9347 | 0.9337 |
+| 0.1895        | 3.0   | 1668 | 0.1562          | 0.9592   | 0.9619    | 0.9592 | 0.9595 |
+| 0.1558        | 4.0   | 2224 | 0.1673          | 0.9627   | 0.9632    | 0.9627 | 0.9625 |
+| 0.1617        | 5.0   | 2780 | 0.1505          | 0.9657   | 0.9659    | 0.9657 | 0.9658 |
+| 0.1394        | 6.0   | 3336 | 0.1359          | 0.9632   | 0.9657    | 0.9632 | 0.9635 |
+| 0.1354        | 7.0   | 3892 | 0.1310          | 0.9725   | 0.9725    | 0.9725 | 0.9725 |
+| 0.1192        | 8.0   | 4448 | 0.1238          | 0.9683   | 0.9699    | 0.9683 | 0.9685 |
+| 0.1096        | 9.0   | 5004 | 0.1222          | 0.9742   | 0.9744    | 0.9742 | 0.9742 |
+| 0.1127        | 10.0  | 5560 | 0.1185          | 0.9728   | 0.9735    | 0.9728 | 0.9729 |
+
+
+### Framework versions
+
+- Transformers 4.45.2
+- Pytorch 2.4.1
+- Datasets 3.0.0
+- Tokenizers 0.20.1

added_tokens.json

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

config.json

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+{
+  "_name_or_path": "microsoft/deberta-v3-large",
+  "architectures": [
+    "DebertaV2ForSequenceClassification"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 1024,
+  "initializer_range": 0.02,
+  "intermediate_size": 4096,
+  "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": "4.45.2",
+  "type_vocab_size": 0,
+  "vocab_size": 128100
+}

logs/events.out.tfevents.1748262218.ADAPT-CLIN.1149777.0

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model.safetensors

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special_tokens_map.json

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spm.model

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tokenizer_config.json

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+{
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+  "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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