
# bert-base-multilingual-cased-hebban-reviews

# Dataset
- dataset_name: BramVanroy/hebban-reviews
- dataset_config: filtered_sentiment
- dataset_revision: 2.0.0
- labelcolumn: review_sentiment
- textcolumn: review_text_without_quotes

# Training
- optim: adamw_hf
- learning_rate: 5e-05
- per_device_train_batch_size: 64
- per_device_eval_batch_size: 64
- gradient_accumulation_steps: 1
- max_steps: 5001
- save_steps: 500
- metric_for_best_model: qwk

# Best checkedpoint based on validation
- best_metric: 0.6828581526810108
- best_model_checkpoint: trained/hebban-reviews/bert-base-multilingual-cased/checkpoint-1500

# Test results of best checkpoint
- accuracy: 0.7764792899408284
- f1: 0.7821329848271866
- precision: 0.7907660190770787
- qwk: 0.6813121109021326
- recall: 0.7764792899408284

## Confusion matrix

![cfm](fig/test_confusion_matrix.png)

## Normalized confusion matrix

![norm cfm](fig/test_confusion_matrix_norm.png)

# Environment
- cuda_capabilities: 8.0; 8.0
- cuda_device_count: 2
- cuda_devices: NVIDIA A100-SXM4-80GB; NVIDIA A100-SXM4-80GB
- finetuner_commit: 66294c815326c93682003119534cb72009f558c2
- platform: Linux-4.18.0-305.49.1.el8_4.x86_64-x86_64-with-glibc2.28
- python_version: 3.9.5
- toch_version: 1.10.0
- transformers_version: 4.21.0


{"language": ["nl"], "license": "mit", "tags": ["sentiment-analysis", "dutch", "text"], "datasets": ["BramVanroy/hebban-reviews"], "metrics": ["accuracy", "f1", "precision", "qwk", "recall"], "widget": [{"text": "Wauw, wat een leuk boek! Ik heb me er er goed mee vermaakt."}, {"text": "Nee, deze vond ik niet goed. De auteur doet zijn best om je als lezer mee te trekken in het verhaal maar mij overtuigt het alleszins niet."}, {"text": "Ik vind het niet slecht maar de schrijfstijl trekt me ook niet echt aan. Het wordt een beetje saai vanaf het vijfde hoofdstuk"}], "model-index": [{"name": "bert-base-multilingual-cased-hebban-reviews", "results": [{"task": {"type": "text-classification", "name": "sentiment analysis"}, "dataset": {"name": "BramVanroy/hebban-reviews - filtered_sentiment - 2.0.0", "type": "BramVanroy/hebban-reviews", "config": "filtered_sentiment", "split": "test", "revision": "2.0.0"}, "metrics": [{"type": "accuracy", "value": 0.7764792899408284, "name": "Test accuracy"}, {"type": "f1", "value": 0.7821329848271866, "name": "Test f1"}, {"type": "precision", "value": 0.7907660190770787, "name": "Test precision"}, {"type": "qwk", "value": 0.6813121109021326, "name": "Test qwk"}, {"type": "recall", "value": 0.7764792899408284, "name": "Test recall"}]}]}]}
transformers pytorch tensorboard safetensors bert text-classification sentiment-analysis dutch text nl dataset:BramVanroy/hebban-reviews license:mit model-index autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #safetensors #bert #text-classification #sentiment-analysis #dutch #text #nl #dataset-BramVanroy/hebban-reviews #license-mit #model-index #autotrain_compatible #endpoints_compatible #region-us 


# bert-base-multilingual-cased-hebban-reviews

# Dataset
- dataset_name: BramVanroy/hebban-reviews
- dataset_config: filtered_sentiment
- dataset_revision: 2.0.0
- labelcolumn: review_sentiment
- textcolumn: review_text_without_quotes

# Training
- optim: adamw_hf
- learning_rate: 5e-05
- per_device_train_batch_size: 64
- per_device_eval_batch_size: 64
- gradient_accumulation_steps: 1
- max_steps: 5001
- save_steps: 500
- metric_for_best_model: qwk

# Best checkedpoint based on validation
- best_metric: 0.6828581526810108
- best_model_checkpoint: trained/hebban-reviews/bert-base-multilingual-cased/checkpoint-1500

# Test results of best checkpoint
- accuracy: 0.7764792899408284
- f1: 0.7821329848271866
- precision: 0.7907660190770787
- qwk: 0.6813121109021326
- recall: 0.7764792899408284

## Confusion matrix

!cfm

## Normalized confusion matrix

!norm cfm

# Environment
- cuda_capabilities: 8.0; 8.0
- cuda_device_count: 2
- cuda_devices: NVIDIA A100-SXM4-80GB; NVIDIA A100-SXM4-80GB
- finetuner_commit: 66294c815326c93682003119534cb72009f558c2
- platform: Linux-4.18.0-305.49.1.el8_4.x86_64-x86_64-with-glibc2.28
- python_version: 3.9.5
- toch_version: 1.10.0
- transformers_version: 4.21.0


# bert-base-multilingual-cased-hebban-reviews # Dataset
- dataset_name: BramVanroy/hebban-reviews
- dataset_config: filtered_sentiment
- dataset_revision: 2.0.0
- labelcolumn: review_sentiment
- textcolumn: review_text_without_quotes # Training
- optim: adamw_hf
- learning_rate: 5e-05
- per_device_train_batch_size: 64
- per_device_eval_batch_size: 64
- gradient_accumulation_steps: 1
- max_steps: 5001
- save_steps: 500
- metric_for_best_model: qwk # Best checkedpoint based on validation
- best_metric: 0.6828581526810108
- best_model_checkpoint: trained/hebban-reviews/bert-base-multilingual-cased/checkpoint-1500 # Test results of best checkpoint
- accuracy: 0.7764792899408284
- f1: 0.7821329848271866
- precision: 0.7907660190770787
- qwk: 0.6813121109021326
- recall: 0.7764792899408284 ## Confusion matrix

!cfm ## Normalized confusion matrix

!norm cfm # Environment
- cuda_capabilities: 8.0; 8.0
- cuda_device_count: 2
- cuda_devices: NVIDIA A100-SXM4-80GB; NVIDIA A100-SXM4-80GB
- finetuner_commit: 66294c815326c93682003119534cb72009f558c2
- platform: Linux-4.18.0-305.49.1.el8_4.x86_64-x86_64-with-glibc2.28
- python_version: 3.9.5
- toch_version: 1.10.0
- transformers_version: 4.21.0
TAGS
#transformers #pytorch #tensorboard #safetensors #bert #text-classification #sentiment-analysis #dutch #text #nl #dataset-BramVanroy/hebban-reviews #license-mit #model-index #autotrain_compatible #endpoints_compatible #region-us 
 # bert-base-multilingual-cased-hebban-reviews # Dataset
- dataset_name: BramVanroy/hebban-reviews
- dataset_config: filtered_sentiment
- dataset_revision: 2.0.0
- labelcolumn: review_sentiment
- textcolumn: review_text_without_quotes # Training
- optim: adamw_hf
- learning_rate: 5e-05
- per_device_train_batch_size: 64
- per_device_eval_batch_size: 64
- gradient_accumulation_steps: 1
- max_steps: 5001
- save_steps: 500
- metric_for_best_model: qwk # Best checkedpoint based on validation
- best_metric: 0.6828581526810108
- best_model_checkpoint: trained/hebban-reviews/bert-base-multilingual-cased/checkpoint-1500 # Test results of best checkpoint
- accuracy: 0.7764792899408284
- f1: 0.7821329848271866
- precision: 0.7907660190770787
- qwk: 0.6813121109021326
- recall: 0.7764792899408284 ## Confusion matrix

!cfm ## Normalized confusion matrix

!norm cfm # Environment
- cuda_capabilities: 8.0; 8.0
- cuda_device_count: 2
- cuda_devices: NVIDIA A100-SXM4-80GB; NVIDIA A100-SXM4-80GB
- finetuner_commit: 66294c815326c93682003119534cb72009f558c2
- platform: Linux-4.18.0-305.49.1.el8_4.x86_64-x86_64-with-glibc2.28
- python_version: 3.9.5
- toch_version: 1.10.0
- transformers_version: 4.21.0
passage: TAGS
#transformers #pytorch #tensorboard #safetensors #bert #text-classification #sentiment-analysis #dutch #text #nl #dataset-BramVanroy/hebban-reviews #license-mit #model-index #autotrain_compatible #endpoints_compatible #region-us 
# bert-base-multilingual-cased-hebban-reviews# Dataset
- dataset_name: BramVanroy/hebban-reviews
- dataset_config: filtered_sentiment
- dataset_revision: 2.0.0
- labelcolumn: review_sentiment
- textcolumn: review_text_without_quotes# Training
- optim: adamw_hf
- learning_rate: 5e-05
- per_device_train_batch_size: 64
- per_device_eval_batch_size: 64
- gradient_accumulation_steps: 1
- max_steps: 5001
- save_steps: 500
- metric_for_best_model: qwk# Best checkedpoint based on validation
- best_metric: 0.6828581526810108
- best_model_checkpoint: trained/hebban-reviews/bert-base-multilingual-cased/checkpoint-1500# Test results of best checkpoint
- accuracy: 0.7764792899408284
- f1: 0.7821329848271866
- precision: 0.7907660190770787
- qwk: 0.6813121109021326
- recall: 0.7764792899408284## Confusion matrix

!cfm## Normalized confusion matrix

!norm cfm