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Graimond/
ECBERT-base

Name: ECBERT-base
Rating: 2.5 (8 reviews)

safetensors

modernbert

answerdotai/ModernBERT-base

finetune

apache-2.0

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ECBERT-base

This model is a fine-tuned version of answerdotai/ModernBERT-base on Gorodnichenko, Y., Pham, T., & Talavera, O. (2023). Data and Code for: The Voice of Monetary Policy (Version v1) [Dataset]. ICPSR - Interuniversity Consortium for Political and Social Research. https://doi.org/10.3886/E178302V1. It achieves the following results on the evaluation set:

Loss: 0.4662
Accuracy: 84.34%

The label_map is as follows: {"hawkish": 0, "neutral": 1, "dovish": 2}

Training and evaluation data

Gorodnichenko, Y., Pham, T., & Talavera, O. (2023). Data and Code for: The Voice of Monetary Policy (Version v1) [Dataset]. ICPSR - Interuniversity Consortium for Political and Social Research. https://doi.org/10.3886/E178302V1.

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

learning_rate: 5e-5
train_batch_size: 16
eval_batch_size: 8
seed: 42
lr_scheduler_type: linear
epochs: 10
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss
No log	1	63	0.9462559819221497
1.0232	1.5873	100	N/A
No log	2	126	0.5972977876663208
No log	3	189	0.4892125129699707
0.5002	3.1746	200	N/A
No log	4	252	0.4661949574947357
0.2978	4.7619	300	N/A
No log	5	315	0.4729757606983185
No log	6	378	0.6107903718948364
0.2891	6.34921	400	N/A
No log	7	441	0.49726468324661255
0.2692	7.93651	500	N/A
No log	8	504	0.4903869032859802
No log	9	567	0.568524956703186
0.1863	9.52381	600	N/A
No log	10	630	0.6198205351829529
No log	10	630	0.4661949574947357

Framework versions

Transformers 4.48.0.dev0
Pytorch 2.5.1+cu121
Datasets 3.2.0
Tokenizers 0.21.0

Graimond/ECBERT-base