The spanishulmfit from fpingham

Availability backbone model

Hi!

Thanks for your effort, seems very promising.

However, I got stuck with getting the backbone model in "Load Encoder Weights for Language Model" section. How could I get this backbone model?

in addition, a couple suggestions for reproducibility of notebook:

The spacy model for Spanish needs to be downloaded:

!python -m spacy download es

And a link to the dataset would be cool:

http://www.sepln.org/workshops/tass/tass_data/download.php?auth=ntcabsQs44XedvseKre

I'm trying to replicate in Google Colab your work, right now available here:

https://github.com/danielcanueto/misc/blob/master/Spanish_GeneralTASSv2.ipynb

When this Colab is finished; i'll let you know and cite you as the responsible of this work.

Thanks!

Daniel

TASS Dataset

Hello,

Could you please provide the TASS dataset? I have submitted the form in the link provided in the repo but there is no response.

Thanks,
Satyaki

Hi, I'm trying to use your model, thanks for getting it available. I'm facing this issue: torch is finding a .pth file for de model, not a .h5. I'm new with torch but I think it's due to versions issue. I tried to convert the .h5 file to .pth with:

def convert(path_to_old_model, path_to_save_converted_model):
    """
    path_to_old_model is the path to old model 
    and 
    path_to_save_converted_model is the path where the converted model is stored
    """
    old_wgts = torch.load(path_to_old_model, map_location=lambda storage, loc: storage)
    new_wgts = OrderedDict()
    new_wgts['0.encoder.weight']=old_wgts['0.encoder.weight']
    new_wgts['encoder_dp.emb.weight']=old_wgts['0.encoder_with_dropout.embed.weight']
    new_wgts['rnns.0.weight_hh_l0_raw']=old_wgts['0.rnns.0.module.weight_hh_l0_raw']
    new_wgts['rnns.0.module.weight_ih_l0']=old_wgts['0.rnns.0.module.weight_ih_l0']
    new_wgts['rnns.0.module.weight_hh_l0']=old_wgts['0.rnns.0.module.weight_hh_l0_raw']
    new_wgts['rnns.0.module.bias_ih_l0']=old_wgts['0.rnns.0.module.bias_ih_l0']
    new_wgts['rnns.0.module.bias_hh_l0']=old_wgts['0.rnns.0.module.bias_hh_l0']
    new_wgts['rnns.1.weight_hh_l0_raw']=old_wgts['0.rnns.1.module.weight_hh_l0_raw']
    new_wgts['rnns.1.module.weight_ih_l0']=old_wgts['0.rnns.1.module.weight_ih_l0']
    new_wgts['rnns.1.module.weight_hh_l0']=old_wgts['0.rnns.1.module.weight_hh_l0_raw']
    new_wgts['rnns.1.module.bias_ih_l0']=old_wgts['0.rnns.1.module.bias_ih_l0']
    new_wgts['rnns.1.module.bias_hh_l0']=old_wgts['0.rnns.1.module.bias_hh_l0']
    new_wgts['rnns.2.weight_hh_l0_raw']=old_wgts['0.rnns.2.module.weight_hh_l0_raw']
    new_wgts['rnns.2.module.weight_ih_l0']=old_wgts['0.rnns.2.module.weight_ih_l0']
    new_wgts['rnns.2.module.weight_hh_l0']=old_wgts['0.rnns.2.module.weight_hh_l0_raw']
    new_wgts['rnns.2.module.bias_ih_l0']=old_wgts['0.rnns.2.module.bias_ih_l0']
    new_wgts['rnns.2.module.bias_hh_l0']=old_wgts['0.rnns.2.module.bias_hh_l0']

    torch.save(new_wgts, path_to_save_converted_model+'converted_model.pth')

but then i'm getting the error KeyError: '1.decoder.bias'. Could you help me with this please?

thanks!

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