wavlm-base-emo-fi / hyperparams.yaml
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# ############################################################################
# Model: WAV2VEC base for Emotion Recognition
# ############################################################################
# Hparams NEEDED
HPARAMS_NEEDED: ["encoder_dim", "out_n_neurons", "label_encoder", "softmax"]
# Modules Needed
MODULES_NEEDED: ["wav2vec2", "avg_pool", "output_mlp"]
# Feature parameters
wav2vec2_hub: microsoft/wavlm-base-plus-sv
# Pretrain folder (HuggingFace)
pretrained_path: Porjaz/wavlm-base-emo-fi
# parameters
encoder_dim: 768
out_n_neurons: 5
wav2vec2: !new:speechbrain.lobes.models.huggingface_transformers.wav2vec2.Wav2Vec2
source: !ref <wav2vec2_hub>
output_norm: True
freeze: True
save_path: wav2vec2_checkpoints
avg_pool: !new:speechbrain.nnet.pooling.StatisticsPooling
return_std: False
label_lin: !new:speechbrain.nnet.linear.Linear
input_size: !ref <encoder_dim>
n_neurons: !ref <out_n_neurons>
bias: False
model: !new:torch.nn.ModuleList
- [!ref <label_lin>]
modules:
wav2vec2: !ref <wav2vec2>
label_lin: !ref <label_lin>
avg_pool: !ref <avg_pool>
softmax: !new:speechbrain.nnet.activations.Softmax
label_encoder: !new:speechbrain.dataio.encoder.CategoricalEncoder
pretrainer: !new:speechbrain.utils.parameter_transfer.Pretrainer
loadables:
wav2vec2: !ref <wav2vec2>
model: !ref <model>
label_encoder: !ref <label_encoder>
paths:
wav2vec2: !ref <pretrained_path>/wav2vec2.ckpt
model: !ref <pretrained_path>/model.ckpt
label_encoder: !ref <pretrained_path>/label_encoder.txt