End of training

README.md

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+---
+library_name: transformers
+license: mit
+base_model: deepset/gbert-large
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- f1
+model-index:
+- name: task2_flausch_classification_gbert-large_span_classifier_with_nonspan
+  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. -->
+
+# task2_flausch_classification_gbert-large_span_classifier_with_nonspan
+
+This model is a fine-tuned version of [deepset/gbert-large](https://huggingface.co/deepset/gbert-large) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.2307
+- Accuracy: 0.9479
+- F1: 0.9467
+
+## 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: 16
+- eval_batch_size: 16
+- 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: 3
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch  | Step  | Validation Loss | Accuracy | F1     |
+|:-------------:|:------:|:-----:|:---------------:|:--------:|:------:|
+| 0.3749        | 0.2697 | 1000  | 0.3099          | 0.9149   | 0.9174 |
+| 0.2804        | 0.5394 | 2000  | 0.2330          | 0.9371   | 0.9305 |
+| 0.2672        | 0.8091 | 3000  | 0.2369          | 0.9391   | 0.9339 |
+| 0.2248        | 1.0787 | 4000  | 0.2295          | 0.9427   | 0.9406 |
+| 0.1942        | 1.3484 | 5000  | 0.2244          | 0.9452   | 0.9422 |
+| 0.1873        | 1.6181 | 6000  | 0.2310          | 0.9423   | 0.9393 |
+| 0.1768        | 1.8878 | 7000  | 0.2155          | 0.9469   | 0.9450 |
+| 0.1443        | 2.1575 | 8000  | 0.2295          | 0.9454   | 0.9449 |
+| 0.1198        | 2.4272 | 9000  | 0.2295          | 0.9484   | 0.9474 |
+| 0.1238        | 2.6969 | 10000 | 0.2278          | 0.9479   | 0.9469 |
+| 0.1166        | 2.9666 | 11000 | 0.2307          | 0.9479   | 0.9467 |
+
+
+### Framework versions
+
+- Transformers 4.52.4
+- Pytorch 2.6.0+cu124
+- Datasets 2.14.4
+- Tokenizers 0.21.1

config.json

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+{
+  "architectures": [
+    "BertForSequenceClassification"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "classifier_dropout": null,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 1024,
+  "id2label": {
+    "0": "not",
+    "1": "compliment",
+    "2": "ambiguous",
+    "3": "positive feedback",
+    "4": "affection declaration",
+    "5": "encouragement",
+    "6": "implicit",
+    "7": "agreement",
+    "8": "group membership",
+    "9": "gratitude",
+    "10": "sympathy"
+  },
+  "initializer_range": 0.02,
+  "intermediate_size": 4096,
+  "label2id": {
+    "affection declaration": 4,
+    "agreement": 7,
+    "ambiguous": 2,
+    "compliment": 1,
+    "encouragement": 5,
+    "gratitude": 9,
+    "group membership": 8,
+    "implicit": 6,
+    "not": 0,
+    "positive feedback": 3,
+    "sympathy": 10
+  },
+  "layer_norm_eps": 1e-12,
+  "max_position_embeddings": 512,
+  "model_type": "bert",
+  "num_attention_heads": 16,
+  "num_hidden_layers": 24,
+  "pad_token_id": 0,
+  "position_embedding_type": "absolute",
+  "problem_type": "single_label_classification",
+  "torch_dtype": "float32",
+  "transformers_version": "4.52.4",
+  "type_vocab_size": 2,
+  "use_cache": true,
+  "vocab_size": 31102
+}

model.safetensors

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+oid sha256:eaeb707b7bbed0f1235241b001999fac52a336754c9bccb3e9c068600e474656
+size 1343035348

special_tokens_map.json

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+{
+  "cls_token": "[CLS]",
+  "mask_token": "[MASK]",
+  "pad_token": "[PAD]",
+  "sep_token": "[SEP]",
+  "unk_token": "[UNK]"
+}

tokenizer_config.json

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+{
+  "added_tokens_decoder": {
+    "0": {
+      "content": "[PAD]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "101": {
+      "content": "[UNK]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "102": {
+      "content": "[CLS]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "103": {
+      "content": "[SEP]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "104": {
+      "content": "[MASK]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    }
+  },
+  "clean_up_tokenization_spaces": true,
+  "cls_token": "[CLS]",
+  "do_basic_tokenize": true,
+  "do_lower_case": false,
+  "extra_special_tokens": {},
+  "mask_token": "[MASK]",
+  "max_len": 512,
+  "model_max_length": 512,
+  "never_split": null,
+  "pad_token": "[PAD]",
+  "sep_token": "[SEP]",
+  "strip_accents": false,
+  "tokenize_chinese_chars": true,
+  "tokenizer_class": "BertTokenizer",
+  "unk_token": "[UNK]"
+}

training_args.bin

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+size 5368