Initial Commit

README.md

@@ -0,0 +1,102 @@
+---
+license: mit
+base_model: xlm-roberta-base
+tags:
+- generated_from_trainer
+datasets:
+- hate_speech_filipino
+metrics:
+- accuracy
+- f1
+model-index:
+- name: scenario-non-kd-from-scratch-data-hate_speech_filipino-model-xlm-roberta-base
+  results:
+  - task:
+      name: Text Classification
+      type: text-classification
+    dataset:
+      name: hate_speech_filipino
+      type: hate_speech_filipino
+      config: default
+      split: validation
+      args: default
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.7247164461247637
+    - name: F1
+      type: f1
+      value: 0.7256887214504355
+---
+
+<!-- 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. -->
+
+# scenario-non-kd-from-scratch-data-hate_speech_filipino-model-xlm-roberta-base
+
+This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on the hate_speech_filipino dataset.
+It achieves the following results on the evaluation set:
+- Loss: 1.0612
+- Accuracy: 0.7247
+- F1: 0.7257
+
+## 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: 32
+- eval_batch_size: 32
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 6969
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
+| No log        | 0.32  | 100  | 0.6595          | 0.6307   | 0.6853 |
+| No log        | 0.64  | 200  | 0.5676          | 0.7032   | 0.6620 |
+| No log        | 0.96  | 300  | 0.5294          | 0.7358   | 0.7069 |
+| No log        | 1.28  | 400  | 0.5112          | 0.7493   | 0.7084 |
+| 0.585         | 1.6   | 500  | 0.5554          | 0.7283   | 0.7420 |
+| 0.585         | 1.92  | 600  | 0.5201          | 0.7349   | 0.6679 |
+| 0.585         | 2.24  | 700  | 0.5838          | 0.7361   | 0.7415 |
+| 0.585         | 2.56  | 800  | 0.5693          | 0.7325   | 0.7421 |
+| 0.585         | 2.88  | 900  | 0.5469          | 0.7517   | 0.7128 |
+| 0.3954        | 3.19  | 1000 | 0.6406          | 0.7509   | 0.7361 |
+| 0.3954        | 3.51  | 1100 | 0.5834          | 0.7401   | 0.7158 |
+| 0.3954        | 3.83  | 1200 | 0.6038          | 0.7538   | 0.7324 |
+| 0.3954        | 4.15  | 1300 | 0.7079          | 0.7436   | 0.7230 |
+| 0.3954        | 4.47  | 1400 | 0.7422          | 0.7474   | 0.7182 |
+| 0.2591        | 4.79  | 1500 | 0.6393          | 0.75     | 0.7307 |
+| 0.2591        | 5.11  | 1600 | 0.7890          | 0.7481   | 0.7307 |
+| 0.2591        | 5.43  | 1700 | 1.0788          | 0.7332   | 0.6651 |
+| 0.2591        | 5.75  | 1800 | 0.8036          | 0.7353   | 0.7157 |
+| 0.2591        | 6.07  | 1900 | 1.0868          | 0.7474   | 0.7167 |
+| 0.1729        | 6.39  | 2000 | 1.3150          | 0.7441   | 0.7027 |
+| 0.1729        | 6.71  | 2100 | 1.0097          | 0.7351   | 0.7268 |
+| 0.1729        | 7.03  | 2200 | 1.0160          | 0.7389   | 0.7074 |
+| 0.1729        | 7.35  | 2300 | 1.0612          | 0.7247   | 0.7257 |
+
+
+### Framework versions
+
+- Transformers 4.33.3
+- Pytorch 2.0.1
+- Datasets 2.14.5
+- Tokenizers 0.13.3

config.json

@@ -0,0 +1,29 @@
+{
+  "_name_or_path": "xlm-roberta-base",
+  "architectures": [
+    "XLMRobertaForSequenceClassification"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "bos_token_id": 0,
+  "classifier_dropout": null,
+  "eos_token_id": 2,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 768,
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "layer_norm_eps": 1e-05,
+  "max_position_embeddings": 514,
+  "model_type": "xlm-roberta",
+  "num_attention_heads": 12,
+  "num_hidden_layers": 6,
+  "output_past": true,
+  "pad_token_id": 1,
+  "position_embedding_type": "absolute",
+  "problem_type": "single_label_classification",
+  "torch_dtype": "float32",
+  "transformers_version": "4.33.3",
+  "type_vocab_size": 1,
+  "use_cache": true,
+  "vocab_size": 250002
+}

pytorch_model.bin

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:d4496bd810ae7fa35b270f682577b59925ee72f7a789ebc7a2312bacebea3399
+size 942107569

training_args.bin

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:84bf05bee62a396964cd194818c1f10badbca8c6865459cf981fdcf23914816e
+size 4219