End of training

README.md

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+---
+license: apache-2.0
+base_model: google-bert/bert-large-cased-whole-word-masking
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- f1
+- precision
+- recall
+model-index:
+- name: Intent-classification-BERT-Large-Ashuv5
+  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. -->
+
+# Intent-classification-BERT-Large-Ashuv5
+
+This model is a fine-tuned version of [google-bert/bert-large-cased-whole-word-masking](https://huggingface.co/google-bert/bert-large-cased-whole-word-masking) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 1.7988
+- Accuracy: 0.1420
+- F1: 0.0414
+- Precision: 0.0237
+- Recall: 0.1667
+
+## 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: 0.0005
+- train_batch_size: 16
+- eval_batch_size: 32
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 3
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
+| 2.1123        | 0.24  | 10   | 1.8066          | 0.2174   | 0.0595 | 0.0362    | 0.1667 |
+| 1.8577        | 0.49  | 20   | 1.9500          | 0.1242   | 0.0368 | 0.0207    | 0.1667 |
+| 1.8864        | 0.73  | 30   | 1.7999          | 0.1801   | 0.0509 | 0.0300    | 0.1667 |
+| 1.8516        | 0.98  | 40   | 1.8570          | 0.1429   | 0.0417 | 0.0238    | 0.1667 |
+| 1.8664        | 1.22  | 50   | 1.8667          | 0.1242   | 0.0368 | 0.0207    | 0.1667 |
+| 1.8207        | 1.46  | 60   | 1.9616          | 0.1180   | 0.0352 | 0.0197    | 0.1667 |
+| 1.8652        | 1.71  | 70   | 1.7831          | 0.2174   | 0.0595 | 0.0362    | 0.1667 |
+| 1.8372        | 1.95  | 80   | 1.8018          | 0.2174   | 0.0595 | 0.0362    | 0.1667 |
+| 1.8671        | 2.2   | 90   | 1.8436          | 0.1180   | 0.0352 | 0.0197    | 0.1667 |
+| 1.8484        | 2.44  | 100  | 1.7722          | 0.2174   | 0.0595 | 0.0362    | 0.1667 |
+| 1.8262        | 2.68  | 110  | 1.7752          | 0.2174   | 0.0595 | 0.0362    | 0.1667 |
+| 1.8292        | 2.93  | 120  | 1.8064          | 0.1242   | 0.0368 | 0.0207    | 0.1667 |
+
+
+### Framework versions
+
+- Transformers 4.38.2
+- Pytorch 2.1.2
+- Datasets 2.1.0
+- Tokenizers 0.15.2

config.json

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+{
+  "_name_or_path": "google-bert/bert-large-cased-whole-word-masking",
+  "architectures": [
+    "BertForSequenceClassification"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "classifier_dropout": null,
+  "directionality": "bidi",
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 1024,
+  "id2label": {
+    "0": "Install",
+    "1": "Change",
+    "2": "No Match",
+    "3": "SBC",
+    "4": "Terminate",
+    "5": "Compensation"
+  },
+  "initializer_range": 0.02,
+  "intermediate_size": 4096,
+  "label2id": {
+    "Change": 1,
+    "Compensation": 5,
+    "Install": 0,
+    "No Match": 2,
+    "SBC": 3,
+    "Terminate": 4
+  },
+  "layer_norm_eps": 1e-12,
+  "max_position_embeddings": 512,
+  "model_type": "bert",
+  "num_attention_heads": 16,
+  "num_hidden_layers": 24,
+  "pad_token_id": 0,
+  "pooler_fc_size": 768,
+  "pooler_num_attention_heads": 12,
+  "pooler_num_fc_layers": 3,
+  "pooler_size_per_head": 128,
+  "pooler_type": "first_token_transform",
+  "position_embedding_type": "absolute",
+  "problem_type": "single_label_classification",
+  "torch_dtype": "float32",
+  "transformers_version": "4.38.2",
+  "type_vocab_size": 2,
+  "use_cache": true,
+  "vocab_size": 28996
+}

model.safetensors

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+size 1334388664

training_args.bin

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