Dealing with same problem.I tried to overfit small dataset and got these results

Not able to interpret the graph,So not able to decide what to do next
code which defines the model
def __init__(self,vocab_len,embed_len,hidden_units,output_units,num_layers,bidirectional,dropout):
        super().__init__()
        self.embedding=nn.Embedding(vocab_len,embed_len)
        
        self.hidden=nn.LSTM(embed_len,hidden_units,
                            num_layers=num_layers,
                            bidirectional=bidirectional,
                            dropout=dropout,
                            batch_first=True)
        
        self.fc=nn.Linear(2*hidden_units,output_units)
        
        self.act=nn.Sigmoid()
        
    def forward(self,text,text_len):
        
        embed=self.embedding(text)
        
        packed_embed= nn.utils.rnn.pack_padded_sequence(embed,text_len,batch_first=True)
        
        packed_output,(h_n,c_n)=self.hidden(packed_embed)
        
        hidden=torch.cat((h_n[-2,:,:],h_n[-1,:,:]),dim=1)
        
        dense_outputs=self.fc(hidden)
        
        outputs=self.act(dense_outputs)
        
        return outputs

Any help is much Appreciated