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NTCAL/
norbert2_sentiment_norec_en_gpu_500_rader_max_noder_task

Name: norbert2_sentiment_norec_en_gpu_500_rader_max_noder_task
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#SBATCH --nodes=2

#SBATCH --ntasks-per-node=3

#SBATCH --gres=gpu:A100m40:1

{'train_runtime': 60.0918, 'train_samples_per_second': 41.603, 'train_steps_per_second': 0.166, 'train_loss': 0.6561894416809082, 'epoch': 5.0}

Time: 60.09

Samples/second: 41.60

This model is a fine-tuned version of bert-large-uncased on an unknown dataset. It achieves the following results on the evaluation set:

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The following hyperparameters were used during training:

Training Loss	Epoch	Step	Validation Loss	Compute Metrics	Accuracy	Balanced Accuracy	F1 Score	Recall	Precision
No log	1.0	2	0.6324	:	0.696	0.5	0.8208	1.0	0.696
No log	2.0	4	0.6264	:	0.692	0.4971	0.8180	0.9943	0.6948
No log	3.0	6	0.6180	:	0.696	0.5	0.8208	1.0	0.696
No log	4.0	8	0.6236	:	0.694	0.5023	0.8185	0.9914	0.6970
0.6562	5.0	10	0.6280	:	0.678	0.4889	0.8076	0.9713	0.6912