ncardus/SeqClassifier

README.md

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+---
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- f1
+- precision
+- recall
+model-index:
+- name: BertSeq
+  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. -->
+
+# BertSeq
+
+This model was trained from scratch on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.2244
+- Accuracy: 1.0
+- F1: 1.0
+- Precision: 1.0
+- Recall: 1.0
+
+## 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
+- num_epochs: 50
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1  | Precision | Recall |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:---:|:---------:|:------:|
+| 0.6468        | 2.5   | 5    | 0.5917          | 1.0      | 1.0 | 1.0       | 1.0    |
+| 0.5888        | 5.0   | 10   | 0.5269          | 1.0      | 1.0 | 1.0       | 1.0    |
+| 0.5427        | 7.5   | 15   | 0.4736          | 1.0      | 1.0 | 1.0       | 1.0    |
+| 0.4919        | 10.0  | 20   | 0.4295          | 1.0      | 1.0 | 1.0       | 1.0    |
+| 0.4872        | 12.5  | 25   | 0.3927          | 1.0      | 1.0 | 1.0       | 1.0    |
+| 0.4447        | 15.0  | 30   | 0.3615          | 1.0      | 1.0 | 1.0       | 1.0    |
+| 0.4242        | 17.5  | 35   | 0.3353          | 1.0      | 1.0 | 1.0       | 1.0    |
+| 0.4133        | 20.0  | 40   | 0.3128          | 1.0      | 1.0 | 1.0       | 1.0    |
+| 0.3889        | 22.5  | 45   | 0.2939          | 1.0      | 1.0 | 1.0       | 1.0    |
+| 0.3736        | 25.0  | 50   | 0.2780          | 1.0      | 1.0 | 1.0       | 1.0    |
+| 0.3736        | 27.5  | 55   | 0.2655          | 1.0      | 1.0 | 1.0       | 1.0    |
+| 0.3847        | 30.0  | 60   | 0.2557          | 1.0      | 1.0 | 1.0       | 1.0    |
+| 0.382         | 32.5  | 65   | 0.2483          | 1.0      | 1.0 | 1.0       | 1.0    |
+| 0.3239        | 35.0  | 70   | 0.2418          | 1.0      | 1.0 | 1.0       | 1.0    |
+| 0.3254        | 37.5  | 75   | 0.2361          | 1.0      | 1.0 | 1.0       | 1.0    |
+| 0.3441        | 40.0  | 80   | 0.2316          | 1.0      | 1.0 | 1.0       | 1.0    |
+| 0.3435        | 42.5  | 85   | 0.2284          | 1.0      | 1.0 | 1.0       | 1.0    |
+| 0.3541        | 45.0  | 90   | 0.2262          | 1.0      | 1.0 | 1.0       | 1.0    |
+| 0.2947        | 47.5  | 95   | 0.2248          | 1.0      | 1.0 | 1.0       | 1.0    |
+| 0.3678        | 50.0  | 100  | 0.2244          | 1.0      | 1.0 | 1.0       | 1.0    |
+
+
+### Framework versions
+
+- Transformers 4.35.2
+- Pytorch 2.1.1
+- Tokenizers 0.15.0

config.json

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+{
+  "_name_or_path": "ncardus/TrainedMLM",
+  "architectures": [
+    "BertForSequenceClassification"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "classifier_dropout": null,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 128,
+  "initializer_range": 0.02,
+  "intermediate_size": 1024,
+  "layer_norm_eps": 1e-12,
+  "max_position_embeddings": 512,
+  "model_type": "bert",
+  "num_attention_heads": 8,
+  "num_hidden_layers": 8,
+  "pad_token_id": 0,
+  "position_embedding_type": "absolute",
+  "problem_type": "single_label_classification",
+  "torch_dtype": "float32",
+  "transformers_version": "4.35.2",
+  "type_vocab_size": 2,
+  "use_cache": true,
+  "vocab_size": 256
+}

model.safetensors

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+size 11033176

training_args.bin

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