End of training

README.md

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+---
+library_name: transformers
+license: mit
+base_model: microsoft/Multilingual-MiniLM-L12-H384
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- f1
+model-index:
+- name: m-minilm-l12-h384-booster-finetune
+  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. -->
+
+# m-minilm-l12-h384-booster-finetune
+
+This model is a fine-tuned version of [microsoft/Multilingual-MiniLM-L12-H384](https://huggingface.co/microsoft/Multilingual-MiniLM-L12-H384) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.8722
+- Accuracy: 0.4935
+- F1: 0.6496
+
+## 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: 0.0001
+- train_batch_size: 128
+- eval_batch_size: 256
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 12
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
+| 0.535         | 2.0   | 10   | 0.8722          | 0.4935   | 0.6496 |
+| 0.3502        | 4.0   | 20   | 1.2356          | 0.4124   | 0.5339 |
+| 0.2564        | 6.0   | 30   | 1.2356          | 0.4866   | 0.6418 |
+| 0.2995        | 8.0   | 40   | 1.6847          | 0.3329   | 0.3792 |
+| 0.1545        | 10.0  | 50   | 1.7194          | 0.3423   | 0.3987 |
+| 0.1196        | 12.0  | 60   | 1.6383          | 0.3826   | 0.4877 |
+
+
+### Framework versions
+
+- Transformers 4.44.2
+- Pytorch 2.4.1+cu121
+- Datasets 3.2.0
+- Tokenizers 0.19.1

config.json

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+{
+  "_name_or_path": "microsoft/Multilingual-MiniLM-L12-H384",
+  "architectures": [
+    "BertForSequenceClassification"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "classifier_dropout": null,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 384,
+  "initializer_range": 0.02,
+  "intermediate_size": 1536,
+  "layer_norm_eps": 1e-12,
+  "max_position_embeddings": 512,
+  "model_type": "bert",
+  "num_attention_heads": 12,
+  "num_hidden_layers": 12,
+  "pad_token_id": 0,
+  "position_embedding_type": "absolute",
+  "problem_type": "single_label_classification",
+  "tokenizer_class": "XLMRobertaTokenizer",
+  "torch_dtype": "float32",
+  "transformers_version": "4.44.2",
+  "type_vocab_size": 2,
+  "use_cache": true,
+  "vocab_size": 250037
+}

model.safetensors

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tam_mal_ai_aw_classification_adapter/adapter_config.json

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+{
+  "config": {
+    "architecture": "reft",
+    "dropout": 0.05,
+    "layers": "all",
+    "non_linearity": null,
+    "orthogonality": true,
+    "output_reft": true,
+    "prefix_positions": 3,
+    "r": 1,
+    "suffix_positions": 0,
+    "tied_weights": false
+  },
+  "config_id": "141e29e6c21f7261",
+  "hidden_size": 384,
+  "model_class": "BertAdapterModel",
+  "model_name": "livinNector/m-minilm-l12-h384-data-augumented-dra-tam-mal-aw-classification-finetune",
+  "model_type": "bert",
+  "name": "tam_mal_ai_aw_classification_adapter",
+  "version": "adapters.1.0.1"
+}

tam_mal_ai_aw_classification_adapter/pytorch_adapter.bin

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tam_mal_ai_aw_classification_head/head_config.json

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+{
+  "config": {
+    "activation_function": "ReLU",
+    "bias": true,
+    "dropout_prob": null,
+    "head_type": "classification",
+    "label2id": {
+      "Abusive": 1,
+      "Non-Abusive": 0
+    },
+    "layers": 3,
+    "num_labels": 2,
+    "use_pooler": false
+  },
+  "hidden_size": 384,
+  "model_class": "BertAdapterModel",
+  "model_name": "livinNector/m-minilm-l12-h384-data-augumented-dra-tam-mal-aw-classification-finetune",
+  "model_type": "bert",
+  "name": "tam_mal_ai_aw_classification_head",
+  "version": "adapters.1.0.1"
+}

tam_mal_ai_aw_classification_head/pytorch_model_head.bin

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training_args.bin

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