End of training

README.md

@@ -0,0 +1,85 @@
+---
+base_model: UBC-NLP/MARBERTv2
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+model-index:
+- name: Improved-MARBERT-twitter-sentiment-Twitter
+  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. -->
+
+# Improved-MARBERT-twitter-sentiment-Twitter
+
+This model is a fine-tuned version of [UBC-NLP/MARBERTv2](https://huggingface.co/UBC-NLP/MARBERTv2) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.7706
+- Accuracy: 0.86
+
+## 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: 1e-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: 15
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 0.5838        | 0.55  | 50   | 0.6058          | 0.71     |
+| 0.3547        | 1.1   | 100  | 0.3887          | 0.83     |
+| 0.2792        | 1.65  | 150  | 0.3479          | 0.85     |
+| 0.1929        | 2.2   | 200  | 0.3596          | 0.87     |
+| 0.1725        | 2.75  | 250  | 0.5874          | 0.8      |
+| 0.1342        | 3.3   | 300  | 0.6560          | 0.81     |
+| 0.1179        | 3.85  | 350  | 0.5146          | 0.85     |
+| 0.079         | 4.4   | 400  | 0.6173          | 0.83     |
+| 0.0928        | 4.95  | 450  | 0.7558          | 0.81     |
+| 0.0425        | 5.49  | 500  | 1.0791          | 0.77     |
+| 0.0609        | 6.04  | 550  | 0.7408          | 0.85     |
+| 0.0328        | 6.59  | 600  | 0.8294          | 0.82     |
+| 0.0531        | 7.14  | 650  | 0.6755          | 0.86     |
+| 0.0342        | 7.69  | 700  | 0.6880          | 0.86     |
+| 0.0263        | 8.24  | 750  | 0.7326          | 0.86     |
+| 0.0147        | 8.79  | 800  | 0.8116          | 0.85     |
+| 0.0169        | 9.34  | 850  | 0.8261          | 0.86     |
+| 0.0118        | 9.89  | 900  | 0.7473          | 0.88     |
+| 0.0087        | 10.44 | 950  | 0.7959          | 0.86     |
+| 0.0051        | 10.99 | 1000 | 0.8585          | 0.85     |
+| 0.0086        | 11.54 | 1050 | 0.8035          | 0.87     |
+| 0.0076        | 12.09 | 1100 | 0.8838          | 0.84     |
+| 0.0048        | 12.64 | 1150 | 0.8124          | 0.87     |
+| 0.0095        | 13.19 | 1200 | 0.9262          | 0.85     |
+| 0.0024        | 13.74 | 1250 | 0.8280          | 0.86     |
+| 0.0109        | 14.29 | 1300 | 0.7895          | 0.87     |
+| 0.0038        | 14.84 | 1350 | 0.7706          | 0.86     |
+
+
+### Framework versions
+
+- Transformers 4.34.1
+- Pytorch 2.1.0+cu118
+- Datasets 2.14.7
+- Tokenizers 0.14.1

config.json

@@ -1,7 +1,7 @@
 {
   "_name_or_path": "UBC-NLP/MARBERTv2",
   "architectures": [
-    "BertForMaskedLM"
+    "BertForSequenceClassification"
   ],
   "attention_probs_dropout_prob": 0.1,
   "classifier_dropout": null,
@@ -10,16 +10,8 @@
   "hidden_act": "gelu",
   "hidden_dropout_prob": 0.1,
   "hidden_size": 768,
-  "id2label": {
-    "0": "Negative",
-    "1": "Positive"
-  },
   "initializer_range": 0.02,
   "intermediate_size": 3072,
-  "label2id": {
-    "Negative": 0,
-    "Positive": 1
-  },
   "layer_norm_eps": 1e-12,
   "max_position_embeddings": 512,
   "model_type": "bert",
@@ -32,6 +24,8 @@
   "pooler_size_per_head": 128,
   "pooler_type": "first_token_transform",
   "position_embedding_type": "absolute",
+  "problem_type": "single_label_classification",
+  "torch_dtype": "float32",
   "transformers_version": "4.34.1",
   "type_vocab_size": 2,
   "use_cache": true,