End of training

README.md

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+---
+license: apache-2.0
+base_model: distilbert-base-uncased
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- f1
+- precision
+- recall
+model-index:
+- name: distilbert-12-classes
+  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. -->
+
+# distilbert-12-classes
+
+This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.3754
+- Accuracy: 0.9266
+- F1: 0.9264
+- Precision: 0.9349
+- Recall: 0.9287
+
+## 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-05
+- 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
+- lr_scheduler_warmup_steps: 100
+- num_epochs: 3
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
+| 2.4155        | 0.96  | 50   | 2.1453          | 0.4432   | 0.3707 | 0.5871    | 0.4659 |
+| 1.5038        | 1.92  | 100  | 0.7723          | 0.9261   | 0.9238 | 0.9369    | 0.9402 |
+| 0.4892        | 2.88  | 150  | 0.3246          | 0.9318   | 0.9274 | 0.9356    | 0.9374 |
+
+
+### Framework versions
+
+- Transformers 4.37.2
+- Pytorch 2.1.0+cu121
+- Datasets 2.17.1
+- Tokenizers 0.15.2

config.json

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+{
+  "_name_or_path": "distilbert-base-uncased",
+  "activation": "gelu",
+  "architectures": [
+    "DistilBertForSequenceClassification"
+  ],
+  "attention_dropout": 0.1,
+  "dim": 768,
+  "dropout": 0.1,
+  "hidden_dim": 3072,
+  "id2label": {
+    "0": "YES",
+    "1": "NO",
+    "2": "RIGHT",
+    "3": "LEFT",
+    "4": "FORWARD",
+    "5": "BACK",
+    "6": "HAPPY",
+    "7": "SAD",
+    "8": "SWORD",
+    "9": "BOW",
+    "10": "GO",
+    "11": "STAY"
+  },
+  "initializer_range": 0.02,
+  "label2id": {
+    "BACK": 5,
+    "BOW": 9,
+    "FORWARD": 4,
+    "GO": 10,
+    "HAPPY": 6,
+    "LEFT": 3,
+    "NO": 1,
+    "RIGHT": 2,
+    "SAD": 7,
+    "STAY": 11,
+    "SWORD": 8,
+    "YES": 0
+  },
+  "max_position_embeddings": 512,
+  "model_type": "distilbert",
+  "n_heads": 12,
+  "n_layers": 6,
+  "pad_token_id": 0,
+  "problem_type": "single_label_classification",
+  "qa_dropout": 0.1,
+  "seq_classif_dropout": 0.2,
+  "sinusoidal_pos_embds": false,
+  "tie_weights_": true,
+  "torch_dtype": "float32",
+  "transformers_version": "4.37.2",
+  "vocab_size": 30522
+}

model.safetensors

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+oid sha256:289c5cf7cc8e6dffebe50c3b67c1ec6f6fb069821d6b1eaa9e73e00447f4cb76
+size 267863328

training_args.bin

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